From 46eb55ffb6426e0a22f003e42815254fdb8e3cad Mon Sep 17 00:00:00 2001
From: Vladimir Mandic <mandic00@live.com>
Date: Wed, 17 Mar 2021 14:35:11 -0400
Subject: [PATCH] fix box clamping and raw output

---
 .gitignore                       |    1 +
 CHANGELOG.md                     |    7 +-
 CODE_OF_CONDUCT                  |   21 +
 CONTRIBUTING                     |   20 +
 SECURITY.md                      |    4 +
 dist/demo-browser-index.js       |  640 +--
 dist/demo-browser-index.js.map   |    6 +-
 dist/human.esm-nobundle.js       |   18 +-
 dist/human.esm-nobundle.js.map   |    4 +-
 dist/human.esm.js                |  786 +--
 dist/human.esm.js.map            |    6 +-
 dist/human.js                    |  786 +--
 dist/human.js.map                |    6 +-
 dist/human.node-gpu.js           |   18 +-
 dist/human.node-gpu.js.map       |    4 +-
 dist/human.node.js               |   18 +-
 dist/human.node.js.map           |    4 +-
 dist/tfjs.esm.js                 | 1122 ++---
 dist/tfjs.esm.js.map             |    6 +-
 human.service                    |    4 +-
 package-lock.json                | 7790 ------------------------------
 src/blazeface/facemesh.ts        |   14 +-
 src/draw.ts                      |   11 +-
 src/handpose/handpose.ts         |   16 +-
 src/human.ts                     |   13 +-
 src/nanodet/nanodet.ts           |    8 +-
 typedoc/assets/js/search.js      |    2 +-
 typedoc/classes/human.html       |    7 +-
 typedoc/index.html               |    4 +-
 types/src/draw.d.ts              |    1 +
 types/src/handpose/handpose.d.ts |    1 +
 types/src/human.d.ts             |    1 +
 wiki                             |    2 +-
 33 files changed, 1818 insertions(+), 9533 deletions(-)
 delete mode 100644 package-lock.json

diff --git a/.gitignore b/.gitignore
index 7ddfe6d1..1d2e013f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,3 @@
 node_modules
 private
+pnpm-lock.yaml
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 99d1e3fe..ce8f9a06 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,6 @@
 # @vladmandic/human  
 
-Version: **1.1.7**  
+Version: **1.1.8**  
 Description: **Human: AI-powered 3D Face Detection, Face Embedding & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition**  
 
 Author: **Vladimir Mandic <mandic00@live.com>**  
@@ -11,9 +11,12 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
 
 ### **HEAD -> main** 2021/03/17 mandic00@live.com
 
+- hierarchical readme notes
 
-### **origin/main** 2021/03/17 mandic00@live.com
+### **1.1.8** 2021/03/17 mandic00@live.com
 
+- add experimental nanodet object detection
+- full models signature
 - cleanup
 
 ### **1.1.7** 2021/03/16 mandic00@live.com
diff --git a/CODE_OF_CONDUCT b/CODE_OF_CONDUCT
index 55da76e8..dc9228f4 100644
--- a/CODE_OF_CONDUCT
+++ b/CODE_OF_CONDUCT
@@ -2,3 +2,24 @@
 
 <br>
 
+Use your best judgement  
+If it will possibly make others uncomfortable, do not post it
+
+- Be respectful  
+  Disagreement is not an opportunity to attack someone else's thoughts or opinions. Although views may differ, remember to approach every situation with patience and care
+- Be considerate  
+  Think about how your contribution will affect others in the community
+- Be open minded  
+  Embrace new people and new ideas. Our community is continually evolving and we welcome positive change
+
+Be mindful of your language  
+Any of the following behavior is unacceptable:
+
+- Offensive comments of any kind
+- Threats or intimidation
+- Sexually explicit material
+- Or any other kinds of harassment
+
+If you believe someone is violating the code of conduct, we ask that you report it
+
+Participants asked to stop any harassing behavior are expected to comply immediately  
diff --git a/CONTRIBUTING b/CONTRIBUTING
index 932f8e0c..22137a67 100644
--- a/CONTRIBUTING
+++ b/CONTRIBUTING
@@ -1,3 +1,23 @@
 # Human Library: Contributing Guidelines
 
 <br>
+
+Pull requests from everyone are welcome
+
+<br>
+
+Procedure for contributing:
+- Create a fork of the repository on github  
+  In a top right corner of a GitHub, select "Fork"
+- Clone your forked repository to your local system  
+  `git clone https://github.com/<your-username>/<your-fork>
+- Make your changes  
+- Test your changes against code guidelines  
+  `npm run lint`
+- Push changes to your fork
+- Submit a PR (pull request) to `Human`
+  <https://github.com/vladmandic/human/pulls>
+
+<br>
+
+Your pull request will be reviewed and pending review results, merged into main branch
diff --git a/SECURITY.md b/SECURITY.md
index 9d41451d..8d6959d2 100644
--- a/SECURITY.md
+++ b/SECURITY.md
@@ -1,3 +1,7 @@
 # Human Library: Security Policy
 
 <br>
+
+All issues are tracked publicly on GitHub  
+
+Entire code base and indluded dependencies is automatically scanned against known security vulnerabilities  
diff --git a/dist/demo-browser-index.js b/dist/demo-browser-index.js
index 09206bd9..bdc9b954 100644
--- a/dist/demo-browser-index.js
+++ b/dist/demo-browser-index.js
@@ -5,31 +5,31 @@
   author: <https://github.com/vladmandic>'
   */
 
-var G8=Object.create,Th=Object.defineProperty,q8=Object.getPrototypeOf,X8=Object.prototype.hasOwnProperty,K8=Object.getOwnPropertyNames,Z8=Object.getOwnPropertyDescriptor;var Af=e=>Th(e,"__esModule",{value:!0});var t5=(e,t)=>()=>(t||(t={exports:{}},e(t.exports,t)),t.exports),or=(e,t)=>{for(var n in t)Th(e,n,{get:t[n],enumerable:!0})},Y8=(e,t,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of K8(t))!X8.call(e,r)&&r!=="default"&&Th(e,r,{get:()=>t[r],enumerable:!(n=Z8(t,r))||n.enumerable});return e},Eh=e=>Y8(Af(Th(e!=null?G8(q8(e)):{},"default",e&&e.__esModule&&"default"in e?{get:()=>e.default,enumerable:!0}:{value:e,enumerable:!0})),e);var n5=(e,t,n)=>{if(!t.has(e))throw TypeError("Cannot "+n)},ge=(e,t,n)=>(n5(e,t,"read from private field"),n?n.call(e):t.get(e)),oa=(e,t,n,r)=>(n5(e,t,"write to private field"),r?r.call(e,n):t.set(e,n),n);var G6=t5(j6=>{Af(j6);or(j6,{MediaPipeFaceMesh:()=>Wg,load:()=>ise});var Wg=class{constructor(t,n,r,a){this.facePipeline=new Lg(t,n,r),this.config=a}async estimateFaces(t,n){let r=await this.facePipeline.predict(t,n),a=[];for(let s of r||[]){if(s.isDisposedInternal)continue;let i=s.coords?s.coords.arraySync():[],o=i.map(h=>[h[0]/t.shape[2],h[1]/t.shape[1],h[2]/this.facePipeline.meshSize]),l={};if(i&&i.length>0)for(let h of Object.keys(ea))l[h]=ea[h].map(d=>i[d]);let u=s.box?[Math.max(0,s.box.startPoint[0]),Math.max(0,s.box.startPoint[1]),Math.min(t.shape[1],s.box.endPoint[0])-s.box.startPoint[0],Math.min(t.shape[2],s.box.endPoint[1])-s.box.startPoint[1]]:0,c=s.box?[Math.max(0,s.box.startPoint[0]/t.shape[2]),Math.max(0,s.box.startPoint[1]/t.shape[1]),Math.min(t.shape[1],s.box.endPoint[0]-s.box.startPoint[0])/t.shape[2],Math.min(t.shape[2],s.box.endPoint[1]-s.box.startPoint[1])/t.shape[1]]:[];a.push({confidence:s.faceConfidence||s.boxConfidence||0,boxConfidence:s.boxConfidence,faceConfidence:s.faceConfidence,box:u,mesh:i,boxRaw:c,meshRaw:o,annotations:l,image:s.image?s.image.clone():null}),s.coords&&s.coords.dispose(),s.image&&s.image.dispose()}return a}},Bi=[null,null,null];async function ise(e){Bi=await 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this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let r=this.backend.numDataIds(),a=0;n.forEach(o=>{a+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-t-a-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],r=this.isTapeOn(),a=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=Mf(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Mf(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let A=fd(p,this.backendName);F(A!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),i=()=>{let y=this.backend.numDataIds();o=A.kernelFunc({inputs:f,attrs:m,backend:this.backend});let g=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,y,g);let w=g.map(_=>{if(_.rank!=null)return _;let{dataId:b,shape:x,dtype:N}=_;return this.makeTensorFromDataId(b,x,N)});if(r){let _=this.getTensorsForGradient(p,f,w);n=this.saveTensorsForBackwardMode(_)}return w}}else{let{forwardFunc:p}=e,f=m=>{!r||(n=m.map(A=>this.keep(this.clone(A))))};i=()=>{let m=this.backend.numDataIds();o=this.tidy(()=>p(this.backend,f));let A=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,A),A}}let{inputs:u,attrs:c}=e,h=Mf(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,u,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,u,t,h,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(p=>u[p]!=null?u[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let r=If(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(F(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let 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n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*gf(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 Bu||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*gf(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,a,s){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:a},o=If(e);o!=null&&(r=o.gradFunc),r!=null&&(i.gradient=l=>(l=l.map((u,c)=>{if(u==null){let h=n[c],d=Dh(h.size,h.dtype);return this.makeTensor(d,h.shape,h.dtype)}return u}),r(l.length>1?l:l[0],a,s))),this.state.activeTape.push(i)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=Sf(e),n=new Set(t.map(a=>a.id));for(let a=0;a<this.state.activeScope.track.length;a++){let s=this.state.activeScope.track[a];!s.kept&&!n.has(s.id)&&s.dispose()}let r=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(a=>{!a.kept&&a.scopeId===r.id&&this.track(a)})}gradients(e,t,n,r=!1){if(F(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let a=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));F(a instanceof qe,()=>"The result y returned by f() must be a tensor.");let s=y9(this.state.activeTape,t,a);if(!r&&s.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,u,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,u,t,h,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(p=>u[p]!=null?u[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let r=If(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(F(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let o=n.filter((l,u)=>s[u]);return i.concat(o)}return[]}makeTensor(e,t,n,r){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;let a=e;n==="string"&&Ca(e[0])&&(a=e.map(o=>Pu(o)));let s=r.write(a,t,n),i=new qe(t,n,s,this.nextTensorId());if(this.trackTensor(i,r),n==="string"){let o=this.state.tensorInfo.get(s),l=d5(a);this.state.numBytes+=l-o.bytes,o.bytes=l}return i}makeTensorFromDataId(e,t,n,r){n=n||"float32";let a=new qe(t,n,e,this.nextTensorId());return this.trackTensor(a,r),a}makeVariable(e,t=!0,n,r){n=n||this.nextVariableId().toString(),r!=null&&r!==e.dtype&&(e=e.cast(r));let a=new Vu(e,t,n,this.nextTensorId());if(this.state.registeredVariables[a.name]!=null)throw new Error(`Variable with name ${a.name} was already registered`);return this.state.registeredVariables[a.name]=a,this.incRef(a,this.backend),a}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*gf(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 Vu||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*gf(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,a,s){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:a},o=If(e);o!=null&&(r=o.gradFunc),r!=null&&(i.gradient=l=>(l=l.map((u,c)=>{if(u==null){let h=n[c],d=Oh(h.size,h.dtype);return this.makeTensor(d,h.shape,h.dtype)}return u}),r(l.length>1?l:l[0],a,s))),this.state.activeTape.push(i)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=Sf(e),n=new Set(t.map(a=>a.id));for(let a=0;a<this.state.activeScope.track.length;a++){let s=this.state.activeScope.track[a];!s.kept&&!n.has(s.id)&&s.dispose()}let r=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(a=>{!a.kept&&a.scopeId===r.id&&this.track(a)})}gradients(e,t,n,r=!1){if(F(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let a=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));F(a instanceof qe,()=>"The result y returned by f() must be a tensor.");let s=u9(this.state.activeTape,t,a);if(!r&&s.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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hm=D({ceil_:WN});function BN(e,t,n){let r=C(e,"x","clipByValue");F(t<=n,()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`);let a={x:r},s={clipValueMin:t,clipValueMax:n};return $.runKernel(Ma,a,s)}var Sn=D({clipByValue_:BN});function VN(e){return ot(e,0)}var wx=D({concat1d_:VN});function UN(e,t){return ot(e,t)}var gl=D({concat2d_:UN});function jN(e,t){return ot(e,t)}var bx=D({concat3d_:jN});function HN(e,t){return ot(e,t)}var _x=D({concat4d_:HN});function GN(e,t,n,r,a="NHWC",s=[1,1],i){let o=C(e,"x","conv2d"),l=C(t,"filter","conv2d"),u=o,c=!1;o.rank===3&&(c=!0,u=H(o,[1,o.shape[0],o.shape[1],o.shape[2]])),F(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),F(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),i!=null&&F(Kt(r),()=>`Error in conv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`);let h=a==="NHWC"?u.shape[3]:u.shape[1];F(h===l.shape[2],()=>`Error in conv2d: depth 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oR=D({softmaxCrossEntropy_:iR}),lR={fft:uc,ifft:Nl,rfft:cc,irfft:Xd},uR={hammingWindow:aC,hannWindow:Zx,frame:Yx,stft:lC},Ke={flipLeftRight:dC,resizeNearestNeighbor:rw,resizeBilinear:nw,rotateWithOffset:fC,cropAndResize:cC,nonMaxSuppression:AC,nonMaxSuppressionAsync:kC,nonMaxSuppressionWithScore:NC,nonMaxSuppressionWithScoreAsync:TC,nonMaxSuppressionPadded:CC,nonMaxSuppressionPaddedAsync:FC,transform:OC},sw={bandPart:PC,gramSchmidt:WC,qr:VC},cR={absoluteDifference:HC,computeWeightedLoss:pa,cosineDistance:qC,hingeLoss:KC,huberLoss:YC,logLoss:QC,meanSquaredError:tR,sigmoidCrossEntropy:aR,softmaxCrossEntropy:oR},fa=class extends lx{minimize(e,t=!1,n){let{value:r,grads:a}=this.computeGradients(e,n);if(n!=null){let s=n.map(i=>({name:i.name,tensor:a[i.name]}));this.applyGradients(s)}else this.applyGradients(a);return Re(a),t?r:(r.dispose(),null)}get iterations(){return 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fa{constructor(e,t=.1){super();this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=$.registeredVariables[t];if(this.accumulatedGrads[n]==null){let i=!1;this.accumulatedGrads[n]={originalName:`${t}/accumulator`,variable:L(()=>ec(r.shape,this.initialAccumulatorValue).variable(i))}}let a=Array.isArray(e)?e[n].tensor:e[t];if(a==null)return;let s=this.accumulatedGrads[n].variable;L(()=>{let i=ie(s,ht(a));s.assign(i);let o=ie(O(_e(a,an(ie(i,$.backend.epsilon()))),-this.learningRate),r);r.assign(o)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Re(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)}};ap.className="Adagrad";La(ap);var sp=class extends fa{constructor(e,t,n,r=null){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],L(()=>{this.accBeta1=Ne(t).variable(),this.accBeta2=Ne(n).variable()}),r==null&&(this.epsilon=$.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);L(()=>{let n=be(1,this.accBeta1),r=be(1,this.accBeta2);t.forEach((a,s)=>{let 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Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}};ip.className="Adamax";La(ip);var hc=class extends fa{constructor(e){super();this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=Array.isArray(e)?e[n].tensor:e[t];if(r==null)return;let a=$.registeredVariables[t];L(()=>{let s=ie(O(this.c,r),a);a.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Zt(Ne(-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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SM(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;Ie([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=r,c=R.computePool2DInfo(i.shape,o,l,1,u),h=c.strideHeight,d=c.strideWidth,p=c.filterHeight,f=c.filterWidth,m=c.dilationHeight,A=c.dilationWidth,y=c.effectiveFilterHeight,g=c.effectiveFilterWidth,w=g-1-c.padInfo.left,_=y-1-c.padInfo.top,b=Ue(i.shape,"float32"),x=1/(p*f),N=n.data.get(a.dataId).values,S=Ue(a.shape,"float32",N);for(let T=0;T<c.batchSize;++T)for(let M=0;M<c.inChannels;++M)for(let D=0;D<c.inHeight;++D)for(let z=0;z<c.inWidth;++z){let B=D-_,U=z-w,H=0;for(let X=0;X<y;X+=m){let j=(B+X)/h;if(!(j<0||j>=c.outHeight||Math.floor(j)!==j))for(let ee=0;ee<g;ee+=A){let Y=(U+ee)/d;Y<0||Y>=c.outWidth||Math.floor(Y)!==Y||(H+=S.get(T,j,Y,M))}}b.set(H*x,T,D,z,M)}return n.makeTensorInfo(b.shape,b.dtype,b.values)}var TM={kernelName:Ph,backendName:"cpu",kernelFunc:SM};function 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n.makeTensorInfo(a.shape,a.dtype,m)}var CM={kernelName:Cs,backendName:"cpu",kernelFunc:EM};function RM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;Ie([a],"batchToSpaceND");let o=s.reduce((y,g)=>y*g),l=R.getReshaped(a.shape,s,o),u=R.getPermuted(l.length,s.length),c=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(c,i,s.length),p=bt({inputs:{x:a},backend:n,attrs:{shape:l}}),f=fr({inputs:{x:p},backend:n,attrs:{perm:u}}),m=bt({inputs:{x:f},backend:n,attrs:{shape:c}}),A=ki({inputs:{x:m},backend:n,attrs:{begin:h,size:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var FM={kernelName:wu,backendName:"cpu",kernelFunc:RM};function MM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.data.get(a.dataId).values,l=n.data.get(s.dataId).values,u=jm(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var 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eM={kernelName:xu,backendName:"cpu",kernelFunc:QF},tM=lt(uo,e=>Math.asin(e)),nM={kernelName:uo,backendName:"cpu",kernelFunc:tM},rM=lt(co,e=>Math.asinh(e)),aM={kernelName:co,backendName:"cpu",kernelFunc:rM},sM=lt(ho,e=>Math.atan(e)),iM={kernelName:ho,backendName:"cpu",kernelFunc:sM},oM=zt((e,t)=>Math.atan2(e,t)),lM=Yt(fo,oM),uM={kernelName:fo,backendName:"cpu",kernelFunc:lM},cM=lt(po,e=>Math.atanh(e)),hM={kernelName:po,backendName:"cpu",kernelFunc:cM};function eA(e,t,n,r,a,s){let i=a.strideHeight,o=a.strideWidth,l=a.dilationHeight,u=a.dilationWidth,c=a.effectiveFilterHeight,h=a.effectiveFilterWidth,d=a.padInfo.top,p=a.padInfo.left,f=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=Ue(a.outShape,n),A=m.values,y=a.outShape[1]*a.outShape[2]*a.outShape[3],g=a.outShape[2]*a.outShape[3],w=a.outShape[3];for(let b=0;b<a.batchSize;++b){let _=b*y,x=b*r[0];for(let N=0;N<a.inChannels;++N)for(let T=0;T<a.outHeight;++T){let 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c=R.computePool3DInfo(s.shape,i,o,1,l,u),h=c.strideDepth,d=c.strideHeight,p=c.strideWidth,f=c.filterDepth,m=c.filterHeight,A=c.filterWidth,y=c.dilationDepth,g=c.dilationHeight,w=c.dilationWidth,b=c.effectiveFilterDepth,_=c.effectiveFilterHeight,x=c.effectiveFilterWidth,N=b-1-c.padInfo.front,T=x-1-c.padInfo.left,E=_-1-c.padInfo.top,M=Ue(s.shape,"float32"),z=1/(f*m*A),B=n.bufferSync(a);for(let V=0;V<c.batchSize;++V)for(let U=0;U<c.inChannels;++U)for(let j=0;j<c.inDepth;++j)for(let X=0;X<c.inHeight;++X)for(let G=0;G<c.inWidth;++G){let ee=j-N,Y=X-E,se=G-T,ne=0;for(let le=0;le<b;le+=y){let Q=(ee+le)/h;if(!(Q<0||Q>=c.outDepth||Math.floor(Q)!==Q))for(let pe=0;pe<_;pe+=g){let ue=(Y+pe)/d;if(!(ue<0||ue>=c.outHeight||Math.floor(ue)!==ue))for(let ye=0;ye<x;ye+=w){let me=(se+ye)/p;me<0||me>=c.outWidth||Math.floor(me)!==me||(ne+=B.get(V,Q,ue,me,U))}}}M.set(ne*z,V,j,X,G,U)}return n.makeTensorInfo(M.shape,M.dtype,M.values)}var gM={kernelName:Wh,backendName:"cpu",kernelFunc:yM};function 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n.makeTensorInfo(a.shape,a.dtype,m)}var _M={kernelName:Cs,backendName:"cpu",kernelFunc:bM};function vM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;Ie([a],"batchToSpaceND");let o=s.reduce((y,g)=>y*g),l=R.getReshaped(a.shape,s,o),u=R.getPermuted(l.length,s.length),c=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(c,i,s.length),p=wt({inputs:{x:a},backend:n,attrs:{shape:l}}),f=fr({inputs:{x:p},backend:n,attrs:{perm:u}}),m=wt({inputs:{x:f},backend:n,attrs:{shape:c}}),A=ki({inputs:{x:m},backend:n,attrs:{begin:h,size:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var kM={kernelName:bu,backendName:"cpu",kernelFunc:vM};function IM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.data.get(a.dataId).values,l=n.data.get(s.dataId).values,u=Hm(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var NM={kernelName:Bh,backendName:"cpu",kernelFunc:IM},SM=lt(Ma,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),TM={kernelName:Ma,backendName:"cpu",kernelFunc:SM},EM=e=>{let{x:t}=e.inputs,n=e.backend,r=new Float32Array(v.sizeFromShape(t.shape)),a=n.data.get(t.dataId),s=a.complexTensorInfos.real,i=a.complexTensorInfos.imag,o=n.data.get(s.dataId).values,l=n.data.get(i.dataId).values;for(let u=0;u<o.length;u++){let c=o[u],h=l[u];r[u]=Math.hypot(c,h)}return n.makeOutput(r,t.shape,"float32")},CM={kernelName:_u,backendName:"cpu",kernelFunc:EM};function Rl(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.data.get(r.dataId).complexTensorInfos.imag,s=n.data.get(a.dataId).values;return n.makeTensorInfo(a.shape,a.dtype,s)}var RM={kernelName:td,backendName:"cpu",kernelFunc:Rl};function Fl(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(m=>m.shape),s);if(v.sizeFromShape(i)===0)return 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zM={kernelName:_s,backendName:"cpu",kernelFunc:OM};function PM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r;Ie([a,s],"conv3d");let u=R.computeConv3DInfo(a.shape,s.shape,i,l,o),{filterDepth:c,filterHeight:h,filterWidth:d,dilationDepth:p,dilationHeight:f,dilationWidth:m,padInfo:A}=u,y=A.front,g=A.left,w=A.top,b=new Bt(u.outShape,a.dtype),_=n.data.get(a.dataId).values,x=n.data.get(s.dataId).values,N=b.values,T=v.computeStrides(a.shape),E=v.computeStrides(s.shape);for(let M=0;M<u.batchSize;++M){let z=M*T[0],B=M*b.strides[0];for(let V=0;V<u.outDepth;++V){let U=B+V*b.strides[1],j=V*u.strideDepth-y;for(let X=0;X<c;++X){let G=j+X*p;if(G<0||G>=u.inDepth)continue;let ee=X*E[0],Y=z+G*T[1];for(let se=0;se<u.outHeight;++se){let ne=U+se*b.strides[2],le=se*u.strideHeight-w;for(let Q=0;Q<h;++Q){let pe=le+Q*f;if(pe<0||pe>=u.inHeight)continue;let ue=ee+Q*E[1],ye=Y+pe*T[2];for(let me=0;me<u.outWidth;++me){let Se=ne+me*u.outChannels,Ee=me*u.strideWidth-g;for(let 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JM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.data.get(a.dataId).values,u=n.data.get(s.dataId).values,c=Hm(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=hw(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var QM={kernelName:Gh,backendName:"cpu",kernelFunc:JM};function e$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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a$={kernelName:qh,backendName:"cpu",kernelFunc:r$};function s$(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:c}=r;Ie([a,s],"depthwiseConv2DNativeBackpropInput");let h=v.computeStrides(a.shape),d=v.computeStrides(s.shape),p=R.computeConv2DInfo(c,s.shape,i,o,l,u,!0),f=new Bt(p.inShape,"float32"),m=f.values,[A,y,g]=f.strides,w=n.data.get(a.dataId).values,[b,_,x]=h,N=n.data.get(s.dataId).values,[T,E,M]=d,{batchSize:z,filterHeight:B,filterWidth:V,inChannels:U,inHeight:j,inWidth:X,outChannels:G,outHeight:ee,outWidth:Y,strideHeight:se,strideWidth:ne}=p,le=B-1-p.padInfo.top,Q=V-1-p.padInfo.left,pe=G/U;for(let ue=0;ue<z;++ue)for(let ye=0;ye<U;++ye)for(let me=0;me<j;++me){let Se=me-le,Ee=Math.max(0,Math.ceil(Se/se)),Oe=Math.min(ee,(B+Se)/se);for(let Le=0;Le<X;++Le){let ze=Le-Q,rt=Math.max(0,Math.ceil(ze/ne)),at=Math.min(Y,(V+ze)/ne),ct=0;for(let et=Ee;et<Oe;++et){let mt=et*se-Se;for(let je=rt;je<at;++je){let 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WebGLTexture.")}function db(e,t){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let r=`[${e}x${t}]`;throw new Error("Requested texture size "+r+" is invalid.")}if(e>n||t>n){let r=`[${e}x${t}]`,a=`[${n}x${n}]`;throw new Error("Requested texture size "+r+" greater than WebGL maximum on this browser / GPU "+a+".")}}function pb(e){return ma(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function sA(e,t,n,r,a,s,i){let o=e.getAttribLocation(t,n);return o===-1?!1:(ve(e,()=>e.bindBuffer(e.ARRAY_BUFFER,r)),ve(e,()=>e.vertexAttribPointer(o,a,e.FLOAT,!1,s,i)),ve(e,()=>e.enableVertexAttribArray(o)),!0)}function fb(e,t,n){Nb(e,n),ve(e,()=>e.activeTexture(e.TEXTURE0+n)),ve(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function Ez(e,t){Nb(e,t),ve(e,()=>e.activeTexture(e.TEXTURE0+t)),ve(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function mb(e,t,n){return ma(e,()=>e.getUniformLocation(t,n),'uniform "'+n+'" not present in program.')}function Ab(e,t,n){return e.getUniformLocation(t,n)}function yb(e,t,n,r){ve(e,()=>fb(e,t,r)),ve(e,()=>e.uniform1i(n,r))}function Cz(e){ve(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),ve(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),ve(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function yp(e,t,n){ve(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,n)),ve(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function iA(e,t){ve(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),ve(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function mc(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+gb(e,t))}function gb(e,t){switch(t){case e.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function ma(e,t,n){let r=ve(e,()=>t());if(r==null)throw new Error(n);return r}function Nb(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,r=t+e.TEXTURE0;if(r<e.TEXTURE0||r>n){let a=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${a}.`)}}function Ii(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function Ni(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function gp(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[Ii(e),...Ni(e)]),t}function xb(e,t=!1){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((a,s)=>s>=e.length-2?v.nearestLargerEven(e[s]):e[s]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let r=v.sizeFromShape(e);if(e.length<=1&&r<=n)return[1,r];if(e.length===2&&e[0]<=n&&e[1]<=n)return e;if(e.length===3&&e[0]*e[1]<=n&&e[2]<=n)return[e[0]*e[1],e[2]];if(e.length===3&&e[0]<=n&&e[1]*e[2]<=n)return[e[0],e[1]*e[2]];if(e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n)return[e[0]*e[1]*e[2],e[3]];if(e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n)return[e[0],e[1]*e[2]*e[3]];if(t){let a=Ii(e),s=2,i=2;return e.length&&([s,i]=Ni(e)),r=a*(s/2)*(i/2),v.sizeToSquarishShape(r).map(o=>o*2)}return v.sizeToSquarishShape(r)}function wp(e){return e%2==0}function Ac(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e.slice(-1)[0],r=t.slice(-1)[0];if(n===r||wp(n)&&wp(r)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&wp(e[0])&&wp(t[0])}var bp,_p;function wb(e){if(bp==null){let t=Xr(e);bp=t.getParameter(t.MAX_TEXTURE_SIZE)}return bp}function Rz(){bp=null}function Fz(){_p=null}function bb(e){if(_p==null){let t=Xr(e);_p=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,_p)}function _b(e){if(e===0)return 0;let t,n=Xr(e);return tr(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:tr(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function tr(e,t){return e.getExtension(t)!=null}function oA(e){try{if(Xr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function vb(e){if(e===0)return!1;let t=Xr(e);if(e===1){if(!tr(t,"OES_texture_float"))return!1}else if(!tr(t,"EXT_color_buffer_float"))return!1;return cA(t)}function kb(e){if(e===0)return!1;let t=Xr(e);if(e===1){if(!tr(t,"OES_texture_float")||!tr(t,"WEBGL_color_buffer_float"))return!1}else{if(tr(t,"EXT_color_buffer_float"))return cA(t);let n="EXT_color_buffer_half_float";if(tr(t,n)){let r=t.getExtension(n);return Vz(t,r)}return!1}return cA(t)}function cA(e){let t=uA(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,r,a,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(s),i}function Vz(e,t){let n=uA(e,t),r=e.createTexture();e.bindTexture(e.TEXTURE_2D,r);let a=1,s=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,a,s,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,r,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(r),e.deleteFramebuffer(i),o}function Ib(e){return e!==2?!1:Xr(e).fenceSync!=null}function Ml(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var De=J();De.registerFlag("HAS_WEBGL",()=>De.getNumber("WEBGL_VERSION")>0);De.registerFlag("WEBGL_VERSION",()=>oA(2)?2:oA(1)?1:0);De.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);De.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>De.get("WEBGL_VERSION")===2);De.registerFlag("WEBGL_CPU_FORWARD",()=>!0);De.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);De.registerFlag("WEBGL_PACK",()=>De.getBool("HAS_WEBGL"));De.registerFlag("WEBGL_PACK_NORMALIZATION",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_CLIP",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>!1);De.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_PACK_REDUCE",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_LAZILY_UNPACK",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_CONV_IM2COL",()=>De.getBool("WEBGL_PACK"));De.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>wb(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>bb(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=De.getNumber("WEBGL_VERSION");return e===0?0:_b(e)});De.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>De.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!ju.isMobile());De.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>vb(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>De.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:De.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));De.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>kb(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_FENCE_API_ENABLED",()=>Ib(De.getNumber("WEBGL_VERSION")));De.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>De.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);De.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});De.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>ju.isMobile()&&De.getBool("IS_CHROME")?1:-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});function gn(){let e,t,n,r,a,s,i,o,l,u;return J().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",r="in",a="texture",s="outputColor",i="out vec4 outputColor;",o=`
       bool isnan_custom(float val) {
         return (val > 0.0 || val < 0.0) ? false : val != 0.0;
       }
@@ -78,7 +78,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
   int getFlatIndex(ivec3 coords) {
     return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
   }
-`}var Nb=`
+`}var Sb=`
   const float FLOAT_MAX = 1.70141184e38;
   const float FLOAT_MIN = 1.17549435e-38;
 
@@ -117,7 +117,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
     return c / 255.0;
   }
-`,Yz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Ac.DENSE;let t=gc(e),n=gn();this.outputShape=e,this.userCode=`
+`,Uz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=yc.DENSE;let t=xc(e),n=gn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
         ${Ti(["r","c","d"],e)}
         return ivec3(r, c, d);
@@ -138,7 +138,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},Jz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Ac.DENSE;let t=gc(e),n=gn();this.outputShape=e,this.userCode=`
+    `}},jz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=yc.DENSE;let t=xc(e),n=gn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
         ${Ti(["r","c","d"],e)}
         return ivec3(r, c, d);
@@ -159,22 +159,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},Qz=class{constructor(e){this.variableNames=["A"],this.outTexUsage=nr.DOWNLOAD;let t=gn();this.outputShape=e,this.userCode=`
-      ${Nb}
+    `}},Hz=class{constructor(e){this.variableNames=["A"],this.outTexUsage=nr.DOWNLOAD;let t=gn();this.outputShape=e,this.userCode=`
+      ${Sb}
 
       void main() {
         float x = getAAtOutCoords();
         ${t.output} = encode_float(x);
       }
-    `}},eP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=nr.DOWNLOAD;let t=gn();this.outputShape=e,this.userCode=`
-      ${Nb}
+    `}},Gz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=nr.DOWNLOAD;let t=gn();this.outputShape=e,this.userCode=`
+      ${Sb}
 
       void main() {
         ivec3 coords = getOutputCoords();
         float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
         ${t.output} = encode_float(x);
       }
-    `}},tP=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=gn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
+    `}},qz=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=gn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
       ${hA(e)}
 
       void main() {
@@ -204,7 +204,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = vec4(${i}, 0., 0., 0.);
       }
-    `}},nP=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=gn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let u=0;u<=1;u++){let c=l*2+u;i+=`
+    `}},Xz=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=gn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let u=0;u<=1;u++){let c=l*2+u;i+=`
           localCoords = coords;
           if(localCoords[2] + ${u} < ${e[2]}) {
             localCoords[2] += ${u};
@@ -248,7 +248,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = ${o};
       }
-    `}},Sb={};We(Sb,{bindVertexProgramAttributeStreams:()=>Ob,createBufferFromOutputTexture:()=>Lb,createFloat16MatrixTexture:()=>Fb,createFloat16PackedMatrixTexture:()=>Db,createFloat32MatrixTexture:()=>Rb,createIndexBuffer:()=>Cb,createPackedMatrixTexture:()=>$b,createUnsignedBytesMatrixTexture:()=>Mb,createVertexBuffer:()=>Eb,createVertexShader:()=>Tb,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Bb,downloadFloat32MatrixFromBuffer:()=>Wb,downloadMatrixFromPackedOutputTexture:()=>Ub,downloadPackedMatrixFromBuffer:()=>Vb,getInternalFormatForFloat16MatrixTexture:()=>pA,getInternalFormatForFloat16PackedMatrixTexture:()=>AA,getInternalFormatForFloat32MatrixTexture:()=>dA,getInternalFormatForPackedMatrixTexture:()=>mA,getInternalFormatForUnsignedBytesMatrixTexture:()=>fA,uploadDenseMatrixToTexture:()=>zb,uploadPixelDataToTexture:()=>Pb});function Tb(e){let t=gn(),n=`${t.version}
+    `}},Tb={};We(Tb,{bindVertexProgramAttributeStreams:()=>zb,createBufferFromOutputTexture:()=>Wb,createFloat16MatrixTexture:()=>Mb,createFloat16PackedMatrixTexture:()=>Ob,createFloat32MatrixTexture:()=>Fb,createIndexBuffer:()=>Rb,createPackedMatrixTexture:()=>Db,createUnsignedBytesMatrixTexture:()=>$b,createVertexBuffer:()=>Cb,createVertexShader:()=>Eb,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Vb,downloadFloat32MatrixFromBuffer:()=>Bb,downloadMatrixFromPackedOutputTexture:()=>jb,downloadPackedMatrixFromBuffer:()=>Ub,getInternalFormatForFloat16MatrixTexture:()=>pA,getInternalFormatForFloat16PackedMatrixTexture:()=>AA,getInternalFormatForFloat32MatrixTexture:()=>dA,getInternalFormatForPackedMatrixTexture:()=>mA,getInternalFormatForUnsignedBytesMatrixTexture:()=>fA,uploadDenseMatrixToTexture:()=>Pb,uploadPixelDataToTexture:()=>Lb});function Eb(e){let t=gn(),n=`${t.version}
     precision highp float;
     ${t.attribute} vec3 clipSpacePos;
     ${t.attribute} vec2 uv;
@@ -257,22 +257,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
     void main() {
       gl_Position = vec4(clipSpacePos, 1);
       resultUV = uv;
-    }`;return ab(e,n)}function Eb(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 lb(e,t)}function Cb(e){let t=new Uint16Array([0,1,2,2,1,3]);return ub(e,t)}function xc(e,t,n,r,a,s){hb(t,n);let i=cb(e),o=e.TEXTURE_2D;return ve(e,()=>e.bindTexture(o,i)),ve(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),ve(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),ve(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),ve(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),ve(e,()=>e.texImage2D(o,0,r,t,n,0,a,s,null)),ve(e,()=>e.bindTexture(e.TEXTURE_2D,null)),i}function dA(e){return e.internalFormatFloat}function Rb(e,t,n,r){let[a,s]=yc(t,n);return xc(e,a,s,dA(r),r.textureFormatFloat,e.FLOAT)}function pA(e){return e.internalFormatHalfFloat}function Fb(e,t,n,r){let[a,s]=yc(t,n);return xc(e,a,s,pA(r),r.textureFormatFloat,r.textureTypeHalfFloat)}function fA(e){return e.downloadTextureFormat}function Mb(e,t,n,r){let[a,s]=yc(t,n);return xc(e,a,s,fA(r),e.RGBA,e.UNSIGNED_BYTE)}function mA(e){return e.internalFormatPackedFloat}function $b(e,t,n,r){let[a,s]=$l(t,n);return xc(e,a,s,mA(r),e.RGBA,e.FLOAT)}function AA(e){return e.internalFormatPackedHalfFloat}function Db(e,t,n,r){let[a,s]=$l(t,n);return xc(e,a,s,AA(r),e.RGBA,r.textureTypeHalfFloat)}function Ob(e,t,n){let r=0,a=3*4,s=3*4+2*4;return ve(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),sA(e,t,"clipSpacePos",n,3,s,r)&&sA(e,t,"uv",n,2,s,a)}function zb(e,t,n,r,a,s){ve(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;a instanceof Uint8Array?(i=new Uint8Array(n*r*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(n*r*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(a),ve(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,r,0,e.RGBA,o,i)),ve(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function Pb(e,t,n){ve(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?ve(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):ve(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),ve(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function Lb(e,t,n,r){let a=e.createBuffer();ve(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,a));let s=4*4*t*n;return ve(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),ve(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),ve(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),a}function Wb(e,t,n){let r=e,a=new Float32Array(n);return r.bindBuffer(r.PIXEL_PACK_BUFFER,t),r.getBufferSubData(r.PIXEL_PACK_BUFFER,0,a),r.bindBuffer(r.PIXEL_PACK_BUFFER,null),a}function Bb(e,t,n,r){let[a,s]=yc(t,n),i=4,o=new Uint8Array(Uz(t*n,i));return ve(e,()=>e.readPixels(0,0,a,s,r.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function Vb(e,t,n,r,a,s,i,o){let l=e,u=new Float32Array(Hz(s,i));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 Ub(e,t,n){let r=new Float32Array(t*n*4);return ve(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,r)),r}var _p=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=J().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,gp(t,e)):this.gl=Xr(t);let n="WEBGL_color_buffer_float",r="EXT_color_buffer_half_float";if(J().getNumber("WEBGL_VERSION")===1){let a="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=pc(this.gl,a),tr(this.gl,s))this.textureHalfFloatExtension=pc(this.gl,s);else if(J().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),tr(this.gl,r))this.colorBufferHalfFloatExtension=pc(this.gl,r);else if(J().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",tr(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(tr(this.gl,r))this.colorBufferHalfFloatExtension=this.gl.getExtension(r);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=Eb(this.gl),this.indexBuffer=Cb(this.gl),this.framebuffer=db(this.gl),this.textureConfig=uA(this.gl,this.textureHalfFloatExtension)}get debug(){return J().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. 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this.throwIfDisposed(),Db(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),$b(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(iA(this.gl,this.framebuffer),this.outputTexture=null),ve(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Bb(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,r,a,s){return Vb(this.gl,e,t,n,r,a,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return Wb(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let r=Lb(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(J().getBool("WEBGL_FENCE_API_ENABLED")){let r=e,a=r.fenceSync(r.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let 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ve(t,()=>t.attachShader(a,r)),ve(t,()=>t.attachShader(a,n)),ob(t,a),this.debug&&mp(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=Ob(t,this.program,this.vertexBuffer)),a}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&ve(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&mp(this.gl,this.program),ve(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?fb(this.gl,e,t):mb(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),ve(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return 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this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=pc(this.gl,J().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(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.createQuery();return n.beginQuery(r.TIME_ELAPSED_EXT,a),a}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(J().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 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r=this.gl;Ap(r,e,this.framebuffer),this.debug&&fc(r),this.outputTexture=e,ve(r,()=>r.viewport(0,0,t,n)),ve(r,()=>r.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,r){this.throwIfDisposed(),ve(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 rP(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:Hb}=R;function dP(e,t,n,r){let a=[];e.forEach(p=>{let f=v.sizeFromShape(p.shapeInfo.logicalShape);p.shapeInfo.isUniform?a.push(`uniform float ${p.name}${f>1?`[${f}]`:""};`):(a.push(`uniform sampler2D ${p.name};`),a.push(`uniform int offset${p.name};`))});let s=a.join(`
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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;ve(e,()=>e.finish()),ve(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),ve(e,()=>e.deleteFramebuffer(this.framebuffer)),ve(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),ve(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),ve(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),Fb(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),Mb(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),$b(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),Lb(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,r){this.throwIfDisposed(),Pb(this.gl,e,t,n,r,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),Ob(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),Db(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(iA(this.gl,this.framebuffer),this.outputTexture=null),ve(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Vb(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,r,a,s){return Ub(this.gl,e,t,n,r,a,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return Bb(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let r=Wb(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(J().getBool("WEBGL_FENCE_API_ENABLED")){let r=e,a=r.fenceSync(r.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let s=r.clientWaitSync(a,0,0);return s===r.ALREADY_SIGNALED||s===r.CONDITION_SATISFIED},t=a}else J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>jb(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=ib(t,e),r=Eb(t),a=ob(t);return ve(t,()=>t.attachShader(a,r)),ve(t,()=>t.attachShader(a,n)),lb(t,a),this.debug&&Ap(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=zb(t,this.program,this.vertexBuffer)),a}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&ve(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&Ap(this.gl,this.program),ve(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?mb(this.gl,e,t):Ab(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),ve(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(),yb(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[r,a]=$l(t,n);this.setOutputMatrixTextureDriver(e,r,a)}setOutputMatrixWriteRegion(e,t,n,r){this.setOutputMatrixWriteRegionDriver(n,e,r,t)}setOutputPackedMatrixWriteRegion(e,t,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&Ap(this.gl,this.program),mc(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),ve(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),ve(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=fc(this.gl,J().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(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.createQuery();return n.beginQuery(r.TIME_ELAPSED_EXT,a),a}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),a&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),r=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=Kz(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),yp(this.gl,e,this.framebuffer),this.debug&&mc(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(yp(this.gl,this.outputTexture,this.framebuffer),this.debug&&mc(this.gl)):iA(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;yp(r,e,this.framebuffer),this.debug&&mc(r),this.outputTexture=e,ve(r,()=>r.viewport(0,0,t,n)),ve(r,()=>r.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,r){this.throwIfDisposed(),ve(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 Kz(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:Hb}=R;function aP(e,t,n,r){let a=[];e.forEach(p=>{let f=v.sizeFromShape(p.shapeInfo.logicalShape);p.shapeInfo.isUniform?a.push(`uniform float ${p.name}${f>1?`[${f}]`:""};`):(a.push(`uniform sampler2D ${p.name};`),a.push(`uniform int offset${p.name};`))});let s=a.join(`
+`),i=e.map(p=>Zz(p,t,r)).join(`
+`),o=t.texShape,l=gn(),u=Qz(l),c,h,d=nP(l);return t.isPacked?(c=Yz(t.logicalShape,o),h=tP(l)):(c=Jz(t.logicalShape,o),h=eP(l)),r&&(d+=rP),[d,u,h,s,c,i,n].join(`
+`)}function Dl(e){let t=e.shapeInfo.logicalShape;switch(t.length){case 0:return sP(e);case 1:return iP(e);case 2:return oP(e);case 3:return lP(e);case 4:return uP(e);case 5:return cP(e);case 6:return hP(e);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function Gb(e){switch(e.shapeInfo.logicalShape.length){case 0:return dP(e);case 1:return pP(e);case 2:return fP(e);case 3:return mP(e);default:return AP(e)}}function Zz(e,t,n=!1){let r="";n?r+=Gb(e):r+=Dl(e);let a=e.shapeInfo.logicalShape,s=t.logicalShape;return a.length<=s.length&&(n?r+=yP(e,t):r+=gP(e,t)),r}function Yz(e,t){switch(e.length){case 0:return qb();case 1:return xP(e,t);case 2:return _P(e,t);case 3:return wP(e,t);default:return bP(e,t)}}function Jz(e,t){switch(e.length){case 0:return qb();case 1:return vP(e,t);case 2:return TP(e,t);case 3:return kP(e,t);case 4:return IP(e,t);case 5:return NP(e,t);case 6:return SP(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function Qz(e){return`
     float sampleTexture(sampler2D textureSampler, vec2 uv) {
       return ${e.texture2D}(textureSampler, uv).r;
     }
-  `}function lP(e){return`
+  `}function eP(e){return`
     void setOutput(float val) {
       ${e.output} = vec4(val, 0, 0, 0);
     }
-  `}function uP(e){return`
+  `}function tP(e){return`
     void setOutput(vec4 val) {
       ${e.output} = val;
     }
-  `}function cP(e){return`${e.version}
+  `}function nP(e){return`${e.version}
     precision highp float;
     precision highp int;
     precision highp sampler2D;
@@ -327,10 +327,10 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       return fract((p3.x + p3.y) * p3.z);
     }
 
-    ${zP}
-    ${PP}
-    ${LP}
-  `}var zP=`
+    ${EP}
+    ${CP}
+    ${RP}
+  `}var EP=`
 vec2 uvFromFlat(int texNumR, int texNumC, int index) {
   int texR = index / texNumC;
   int texC = index - texR * texNumC;
@@ -342,7 +342,7 @@ vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,PP=`
+`,CP=`
 vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texNumC, int row, int col) {
   int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
@@ -350,7 +350,7 @@ vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,LP=`
+`,RP=`
 vec2 packedUVfrom3D(int texNumR, int texNumC,
     int texelsInBatch, int texelsInLogicalRow, int b,
     int row, int col) {
@@ -359,7 +359,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   int texC = index - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,hP=`
+`,rP=`
   float getChannel(vec4 frag, vec2 innerDims) {
     vec2 modCoord = mod(innerDims, 2.);
     return modCoord.x == 0. ?
@@ -370,11 +370,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     float modCoord = mod(float(dim), 2.);
     return modCoord == 0. ? frag.r : frag.g;
   }
-`;function Gb(){return`
+`;function qb(){return`
     int getOutputCoords() {
       return 0;
     }
-  `}function SP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
+  `}function xP(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 * ${n[1]}.0);
       }
@@ -388,7 +388,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${n[0]}, ${n[1]}));
       return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
     }
-  `}function RP(e,t){return t[0]===1?`
+  `}function vP(e,t){return t[0]===1?`
       int getOutputCoords() {
         return int(resultUV.x * ${t[1]}.0);
       }
@@ -402,7 +402,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${t[0]}, ${t[1]}));
       return resTexRC.x * ${t[1]} + resTexRC.y;
     }
-  `}function TP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
+  `}function wP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${n[0]}, ${n[1]}));
@@ -416,7 +416,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec3(b, r, c);
     }
-  `}function FP(e,t){let n=Ti(["r","c","d"],e);return`
+  `}function kP(e,t){let n=Ti(["r","c","d"],e);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${t[0]}, ${t[1]}));
@@ -424,7 +424,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec3(r, c, d);
     }
-  `}function EP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
+  `}function bP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
       int b${l} = index / ${s};
       index -= b${l} * ${s};
     `+i,o=`b${l}, `+o;return`
@@ -443,7 +443,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec${e.length}(${o});
     }
-  `}function MP(e,t){let n=Ti(["r","c","d","d2"],e);return`
+  `}function IP(e,t){let n=Ti(["r","c","d","d2"],e);return`
     ivec4 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -451,7 +451,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec4(r, c, d, d2);
     }
-  `}function $P(e,t){let n=Ti(["r","c","d","d2","d3"],e);return`
+  `}function NP(e,t){let n=Ti(["r","c","d","d2","d3"],e);return`
     ivec5 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                              ${t[1]}));
@@ -463,7 +463,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec5 outShape = ivec5(r, c, d, d2, d3);
       return outShape;
     }
-  `}function DP(e,t){let n=Ti(["r","c","d","d2","d3","d4"],e);return`
+  `}function SP(e,t){let n=Ti(["r","c","d","d2","d3","d4"],e);return`
     ivec6 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -474,7 +474,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec6 result = ivec6(r, c, d, d2, d3, d4);
       return result;
     }
-  `}function CP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
+  `}function _P(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
       ivec2 getOutputCoords() {
         return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
       }
@@ -489,7 +489,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec2(r, c);
     }
-  `}function OP(e,t){return v.arraysEqual(e,t)?`
+  `}function TP(e,t){return v.arraysEqual(e,t)?`
       ivec2 getOutputCoords() {
         return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
       }
@@ -516,11 +516,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       int c = index - r * ${e[1]};
       return ivec2(r, c);
     }
-  `}function Ei(e){return`offset${e}`}function wP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=gn();return`
+  `}function Ei(e){return`offset${e}`}function dP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=gn();return`
     vec4 ${n}() {
       return ${r.texture2D}(${t}, halfCR);
     }
-  `}function pP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
+  `}function sP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
       float ${n}() {
         return sampleTexture(${t}, halfCR);
       }
@@ -529,13 +529,13 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${s}, ${i}, ${o});
       return sampleTexture(${t}, uv);
     }
-  `}function bP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=gn();return`
+  `}function pP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=gn();return`
     vec4 ${n}(int index) {
       vec2 uv = packedUVfrom1D(
         ${a[0]}, ${a[1]}, index);
       return ${s.texture2D}(${t}, uv);
     }
-  `}function fP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
+  `}function iP(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
       float ${n}(int index) {
         ${Ol(e)}
       }
@@ -558,7 +558,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${a}, ${s}, index + ${i});
       return sampleTexture(${t}, uv);
     }
-  `}function _P(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=gn();if(a!=null&&v.arraysEqual(t,a))return`
+  `}function fP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=gn();if(a!=null&&v.arraysEqual(t,a))return`
       vec4 ${r}(int row, int col) {
         vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${s}.0);
 
@@ -569,7 +569,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = packedUVfrom2D(${u}, ${l[0]}, ${l[1]}, row, col);
       return ${o.texture2D}(${n}, uv);
     }
-  `}function mP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
+  `}function oP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
     float ${r}(int row, int col) {
       vec2 uv = (vec2(col, row) + halfCR) / vec2(${d}.0, ${h}.0);
       return sampleTexture(${n}, uv);
@@ -603,8 +603,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     vec2 uv = uvFromFlat(${l}, ${u}, index);
     return sampleTexture(${n}, uv);
   }
-`}function vP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=zl(e,h),f=["b","row","col"];return`
-        ${jb(p)}
+`}function mP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=zl(e,h),f=["b","row","col"];return`
+        ${Gb(p)}
         vec4 ${r}(int b, int row, int col) {
           return ${r}(${Pl(f,d)});
         }
@@ -614,7 +614,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         ${i}, ${o}, ${u}, ${l}, b, row, col);
       return ${c.texture2D}(${n}, uv);
     }
-  `}function AP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=zl(e,l),m=["row","col","depth"];return`
+  `}function lP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=zl(e,l),m=["row","col","depth"];return`
         ${Dl(f)}
         float ${r}(int row, int col, int depth) {
           return ${r}(${Pl(m,o)});
@@ -647,7 +647,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         vec2 uv = uvFromFlat(${c}, ${h}, index);
         return sampleTexture(${n}, uv);
       }
-  `}function kP(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],u=Math.ceil(t[n-1]/2),c=u*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,c*=t[n-f-1],d=`b${f} * ${c} + `+d;let p=gn();return`
+  `}function AP(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],u=Math.ceil(t[n-1]/2),c=u*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,c*=t[n-f-1],d=`b${f} * ${c} + `+d;let p=gn();return`
     vec4 ${a}(${h}) {
       int index = ${d};
       int texR = index / ${l};
@@ -655,7 +655,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${o});
       return ${p.texture2D}(${r}, uv);
     }
-  `}function yP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=zl(e,o),m=["row","col","depth","depth2"];return`
+  `}function uP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=zl(e,o),m=["row","col","depth","depth2"];return`
       ${Dl(f)}
       float ${r}(int row, int col, int depth, int depth2) {
         return ${r}(${Pl(m,l)});
@@ -693,7 +693,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${h}, ${d}, index + ${p});
       return sampleTexture(${n}, uv);
     }
-  `}function gP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let m=zl(e,l),A=["row","col","depth","depth2","depth3"];return`
+  `}function cP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let m=zl(e,l),A=["row","col","depth","depth2","depth3"];return`
       ${Dl(m)}
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
         return ${r}(${Pl(A,u)});
@@ -734,7 +734,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${d}, ${p}, index);
       return sampleTexture(${n}, uv);
     }
-  `}function xP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=zl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
+  `}function hP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=zl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
       ${Dl(A)}
       float ${r}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
@@ -790,7 +790,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         return ${t}[i];
       }
     }
-  `}function IP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Hb(e.shapeInfo.logicalShape,t.logicalShape),l=pt(i),u=i-s,c,h=["x","y","z","w","u","v"];s===0?c="":i<2&&o.length>=1?c="coords = 0;":c=o.map(A=>`coords.${h[A+u]} = 0;`).join(`
+  `}function yP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Hb(e.shapeInfo.logicalShape,t.logicalShape),l=dt(i),u=i-s,c,h=["x","y","z","w","u","v"];s===0?c="":i<2&&o.length>=1?c="coords = 0;":c=o.map(A=>`coords.${h[A+u]} = 0;`).join(`
 `);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((A,y)=>`coords.${h[y+u]}`).join(", ");let p="return outputValue;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)p=`
       return vec4(outputValue.xy, outputValue.xy);
     `;else if(f&&!m)i===1?p=`
@@ -804,22 +804,22 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec4 outputValue = get${r}(${d});
       ${p}
     }
-  `}function NP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
+  `}function gP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
       float ${a}() {
         return sampleTexture(${n}, resultUV);
       }
-    `;let u=pt(l),c=Hb(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&c.length>=1?d="coords = 0;":d=c.map(m=>`coords.${p[m+h]} = 0;`).join(`
+    `;let u=dt(l),c=Hb(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&c.length>=1?d="coords = 0;":d=c.map(m=>`coords.${p[m+h]} = 0;`).join(`
 `);let f="";return l<2&&o>0?f="coords":f=e.shapeInfo.logicalShape.map((m,A)=>`coords.${p[A+h]}`).join(", "),`
     float ${a}() {
       ${u} coords = getOutputCoords();
       ${d}
       return get${r}(${f});
     }
-  `}function pt(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function zl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function Pl(e,t){return t.map(n=>e[n]).join(", ")}function WP(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=dP(s,o,a,t.packedInputs),u=e.createProgram(l),c=null,h=e.getUniformLocation(u,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(c=e.getUniformLocation(u,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(u,f,m),d[`offset${f}`]=e.getUniformLocation(u,`offset${f}`,m)}return{program:t,source:l,webGLProgram:u,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:c,nanLoc:h}}function qb(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function BP(e,t,n,r,a){qb(t.inShapeInfos,n),qb([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let u=t.program.variableNames[l],c=t.uniformLocations[u],h=t.uniformLocations[`offset${u}`];if(c!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(c,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(c,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,c,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function VP(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:UP,bincountImpl:Xb,bincountReduceImpl:HP,ceilImpl:jP,concatImpl:GP,expImpl:qP,expm1Impl:XP,floorImpl:KP,gatherV2Impl:ZP,greaterImpl:YP,lessImpl:JP,linSpaceImpl:QP,logImpl:eL,maxImpl:tL,maximumImpl:nL,minimumImpl:rL,multiplyImpl:aL,negImpl:sL,prodImpl:iL,rangeImpl:oL,rsqrtImpl:lL,simpleAbsImpl:Kb,sliceImpl:uL,stridedSliceImpl:cL,subImpl:hL,tileImpl:dL,topKImpl:pL,transposeImpl:yA,uniqueImpl:fL}=Hm;function Zb(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function xn(e,t){return t===1?[e]:Zb(e,t)}function mL(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var xL=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
+  `}function dt(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function zl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function Pl(e,t){return t.map(n=>e[n]).join(", ")}function FP(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=aP(s,o,a,t.packedInputs),u=e.createProgram(l),c=null,h=e.getUniformLocation(u,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(c=e.getUniformLocation(u,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(u,f,m),d[`offset${f}`]=e.getUniformLocation(u,`offset${f}`,m)}return{program:t,source:l,webGLProgram:u,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:c,nanLoc:h}}function Xb(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function MP(e,t,n,r,a){Xb(t.inShapeInfos,n),Xb([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let u=t.program.variableNames[l],c=t.uniformLocations[u],h=t.uniformLocations[`offset${u}`];if(c!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(c,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(c,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,c,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function $P(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:DP,bincountImpl:Kb,bincountReduceImpl:OP,ceilImpl:zP,concatImpl:PP,expImpl:LP,expm1Impl:WP,floorImpl:BP,gatherV2Impl:VP,greaterImpl:UP,lessImpl:jP,linSpaceImpl:HP,logImpl:GP,maxImpl:qP,maximumImpl:XP,minimumImpl:KP,multiplyImpl:ZP,negImpl:YP,prodImpl:JP,rangeImpl:QP,rsqrtImpl:eL,simpleAbsImpl:Zb,sliceImpl:tL,stridedSliceImpl:nL,subImpl:rL,tileImpl:aL,topKImpl:sL,transposeImpl:yA,uniqueImpl:iL}=jm;function Yb(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function xn(e,t){return t===1?[e]:Yb(e,t)}function oL(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var hL=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
         void main() {
           setOutput(vec4(getA(), 0., 0., 0.));
         }
-      `;else{let n=xn("rc",t),r=pt(t),a=AL(t,e,n),s=yL(t,e[e.length-1],e[e.length-2],n),i=gL(e,n);this.userCode=`
+      `;else{let n=xn("rc",t),r=dt(t),a=lL(t,e,n),s=uL(t,e[e.length-1],e[e.length-2],n),i=cL(e,n);this.userCode=`
         void main() {
           ${r} rc = getOutputCoords();
 
@@ -831,7 +831,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             setOutput(vec4(${i}));
           }
         }
-      `}}};function wL(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function AL(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function yL(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
+      `}}};function dL(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function lL(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function uL(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
     int r = ${a[0]};
     int c = ${a[1]};
     int rp1 = r + 1;
@@ -839,12 +839,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
     bool cEdge = cp1 >= ${t};
     bool rEdge = rp1 >= ${n};
-  `}function gL(e,t){let n=e.length,r=wL(n,t);return n===1?`getA(rc),
+  `}function cL(e,t){let n=e.length,r=dL(n,t);return n===1?`getA(rc),
             rc + 1 >= ${e[0]} ? 0. : getA(rc + 1),
             0, 0`:`getA(${r[0]}),
           cEdge ? 0. : getA(${r[1]}),
           rEdge ? 0. : getA(${r[2]}),
-          rEdge || cEdge ? 0. : getA(${r[3]})`}var Yb=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
+          rEdge || cEdge ? 0. : getA(${r[3]})`}var Jb=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
         ${a}
         ${r>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
           int flatIndex = getFlatIndex(thisRC);
@@ -856,7 +856,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
         ${r>0?"}":""}
       `}this.userCode=`
-      ${bL(t)}
+      ${pL(t)}
       ${hA(e)}
 
       void main() {
@@ -872,12 +872,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function bL(e){return`
+    `}};function pL(e){return`
     ivec3 inputCoordsFromReshapedOutCoords(int index) {
       ${Ti(["r","c","d"],e)}
       return ivec3(r, c, d);
     }
-  `}var _L=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=Qb(t,n),a=e_(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=Jb(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===sn.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===sn.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===sn.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===sn.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===sn.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=Qb(n,r),s=e_(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=Jb(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function vL(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function Jb(e,t,n,r,a){let s=kL(t,r),i;if(a){let[l,u]=$l(e[0],e[1]);i=l*u}else{let[l,u]=yc(e[0],e[1]);i=l*u}let o=vL(n,s);return i*o}function kL(e,t){switch(e){case sn.PACKED_2X2_FLOAT32:return mA(t);case sn.PACKED_2X2_FLOAT16:return AA(t);case sn.UNPACKED_FLOAT32:return dA(t);case sn.UNPACKED_FLOAT16:return pA(t);case sn.PACKED_4X1_UNSIGNED_BYTE:return fA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function IL(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?sn.PACKED_2X2_FLOAT32:sn.UNPACKED_FLOAT32:e?sn.PACKED_2X2_FLOAT16:sn.UNPACKED_FLOAT16}function Qb(e,t){if(e===nr.UPLOAD)return sn.PACKED_2X2_FLOAT32;if(e===nr.RENDER||e==null)return IL(t);if(e===nr.DOWNLOAD||e===nr.PIXELS)return sn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function e_(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Xa=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+  `}var fL=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=e_(t,n),a=t_(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=Qb(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===sn.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===sn.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===sn.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===sn.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===sn.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=e_(n,r),s=t_(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=Qb(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function mL(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function Qb(e,t,n,r,a){let s=AL(t,r),i;if(a){let[l,u]=$l(e[0],e[1]);i=l*u}else{let[l,u]=gc(e[0],e[1]);i=l*u}let o=mL(n,s);return i*o}function AL(e,t){switch(e){case sn.PACKED_2X2_FLOAT32:return mA(t);case sn.PACKED_2X2_FLOAT16:return AA(t);case sn.UNPACKED_FLOAT32:return dA(t);case sn.UNPACKED_FLOAT16:return pA(t);case sn.PACKED_4X1_UNSIGNED_BYTE:return fA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function yL(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?sn.PACKED_2X2_FLOAT32:sn.UNPACKED_FLOAT32:e?sn.PACKED_2X2_FLOAT16:sn.UNPACKED_FLOAT16}function e_(e,t){if(e===nr.UPLOAD)return sn.PACKED_2X2_FLOAT32;if(e===nr.RENDER||e==null)return yL(t);if(e===nr.DOWNLOAD||e===nr.PIXELS)return sn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function t_(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Xa=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       float unaryOperation(float x) {
         ${t}
       }
@@ -888,11 +888,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},Nr="if (isnan(x)) return x;",NL="return x;",t_="return abs(x);",SL="return (x >= 0.0) ? x : (exp(x) - 1.0);",TL=Nr+`
+    `}},Nr="if (isnan(x)) return x;",gL="return x;",n_="return abs(x);",xL="return (x >= 0.0) ? x : (exp(x) - 1.0);",wL=Nr+`
   return (x < 0.0) ? 0.0 : x;
-`,EL=Nr+`
+`,bL=Nr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,vp="return x;",CL="return x;",RL=`
+`,kp="return x;",_L="return x;",vL=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -901,7 +901,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,FL=`
+`,kL=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -911,7 +911,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,ML=`
+`,IL=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -932,14 +932,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},$L=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=xn("rc",t),r=pt(t),a=mL(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
+    `}},NL=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=xn("rc",t),r=dt(t),a=oL(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
       void main() {
         ${r} rc = getOutputCoords();
         vec4 packedInput = getA(${a});
 
         setOutput(getChannel(packedInput, ${i}));
       }
-    `}},DL=Gr.whereImpl,OL=1e-7,zL=1e-4,gA={};function PL(e){return e in gA||(gA[e]={}),gA[e]}var LL=128,WL=600;function BL(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*WL/1024/1024}var Wl=class extends mu{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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Xr(J().getNumber("WEBGL_VERSION"));this.binaryCache=PL(J().getNumber("WEBGL_VERSION")),this.gpgpu=new _p(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 _L(this.gpgpu),this.numMBBeforeWarning=BL(),this.texData=new Fh(this,Wr())}nextDataId(){return Wl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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:nr.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,a){if(J().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:nr.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new Ll(i,vp):h=new Xa(i,vp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let c;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);c=R.mergeRealAndImagArrays(h,d)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new Ll(r,vp):p=new Xa(r,vp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let p=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...gc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];c=R.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}u!=null&&this.disposeIntermediateTensorInfo(u);let h=this.convertAndCacheOnCPU(e,c),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Wr().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Ue(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!nb(n))throw J().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...gc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?yp(t):t,o=s?new eP(i):new Qz(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture,u.texShape[0],u.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let 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)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Wr().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=LL){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return DL(e.shape,t)}packedUnaryOp(e,t,n){let r=new Ll(e.shape,t),a=this.compileAndRun(r,[e],n);return Wr().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=Kb(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,t_,e.dtype);let t=new Xa(e.shape,t_),n=this.compileAndRun(t,[e]);return Wr().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return Wr().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new $L(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new xL(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[Ii(e.shape),...Ni(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[Ii(t),...Ni(t)],s=new Yb(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=yp(r),i;n?i=new Jz(s):i=new Yz(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===Ac.DENSE){let m=gc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!mc(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let u={shape:s.shape,texData:i,isUniform:!1},c=VP(e,l,u),h=this.getAndSaveBinary(c,()=>WP(this.gpgpu,e,l,u)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),BP(this.gpgpu,h,l,u,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=W(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(Ne(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?OL:zL}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let c=t.texShape;if(c==null&&(c=gb(n,o),t.texShape=c),a!=null){let h=yp(n),d,p=c[1],f=c[0],m=a instanceof Uint8Array;o?([p,f]=$l(c[0],c[1]),d=new nP(h,[f,p],m)):d=new tP(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=nr.PIXELS:this.texData.get(A.dataId).usage=nr.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-u)}else{let h=this.acquireTexture(c,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=VL(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Wl.nextDataId=0;function VL(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 n_="3.3.0";function r_(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}Uu.isBrowser()&&ml("webgl",()=>new Wl,2);var UL={forceHalfFloat:r_},a_=`
+    `}},SL=Gr.whereImpl,TL=1e-7,EL=1e-4,gA={};function CL(e){return e in gA||(gA[e]={}),gA[e]}var RL=128,FL=600;function ML(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*FL/1024/1024}var Wl=class extends Au{constructor(e){super();if(this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Xr(J().getNumber("WEBGL_VERSION"));this.binaryCache=CL(J().getNumber("WEBGL_VERSION")),this.gpgpu=new vp(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 fL(this.gpgpu),this.numMBBeforeWarning=ML(),this.texData=new Mh(this,Wr())}nextDataId(){return Wl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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:nr.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,a){if(J().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:nr.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new Ll(i,kp):h=new Xa(i,kp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let c;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);c=R.mergeRealAndImagArrays(h,d)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new Ll(r,kp):p=new Xa(r,kp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let p=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...xc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];c=R.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}u!=null&&this.disposeIntermediateTensorInfo(u);let h=this.convertAndCacheOnCPU(e,c),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Wr().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Ue(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!rb(n))throw J().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...xc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?gp(t):t,o=s?new Gz(i):new Hz(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture,u.texShape[0],u.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let 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)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Wr().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=RL){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return SL(e.shape,t)}packedUnaryOp(e,t,n){let r=new Ll(e.shape,t),a=this.compileAndRun(r,[e],n);return Wr().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=Zb(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,n_,e.dtype);let t=new Xa(e.shape,n_),n=this.compileAndRun(t,[e]);return Wr().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return Wr().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new NL(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new hL(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[Ii(e.shape),...Ni(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[Ii(t),...Ni(t)],s=new Jb(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=gp(r),i;n?i=new jz(s):i=new Uz(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===yc.DENSE){let m=xc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!Ac(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let u={shape:s.shape,texData:i,isUniform:!1},c=$P(e,l,u),h=this.getAndSaveBinary(c,()=>FP(this.gpgpu,e,l,u)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),MP(this.gpgpu,h,l,u,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=L(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(Ne(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?TL:EL}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let c=t.texShape;if(c==null&&(c=xb(n,o),t.texShape=c),a!=null){let h=gp(n),d,p=c[1],f=c[0],m=a instanceof Uint8Array;o?([p,f]=$l(c[0],c[1]),d=new Xz(h,[f,p],m)):d=new qz(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=nr.PIXELS:this.texData.get(A.dataId).usage=nr.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-u)}else{let h=this.acquireTexture(c,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=$L(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Wl.nextDataId=0;function $L(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 r_="3.3.0";function a_(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}ju.isBrowser()&&ml("webgl",()=>new Wl,2);var DL={forceHalfFloat:a_},s_=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
 `,Bl=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
@@ -952,17 +952,17 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float b = getBAtOutCoords();
         setOutput(binaryOperation(a, b));
       }
-    `}},kp=`
+    `}},Ip=`
   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;
-`,wc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=R.assertAndGetBroadcastShape(t,n);let a=this.outputShape.length,s="";if(r)if(a===0||v.sizeFromShape(this.outputShape)===1)s=`
+`,bc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=R.assertAndGetBroadcastShape(t,n);let a=this.outputShape.length,s="";if(r)if(a===0||v.sizeFromShape(this.outputShape)===1)s=`
           result.y = 0.;
           result.z = 0.;
           result.w = 0.;
         `;else if(s=`
-          ${pt(a)} coords = getOutputCoords();
+          ${dt(a)} coords = getOutputCoords();
         `,a===1)s+=`
             result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
             result.z = 0.;
@@ -989,21 +989,21 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function Bn(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 HL={kernelName:Fs,backendName:"webgl",kernelFunc:Bn};function Ka(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=Bn({inputs:{x:r},backend:n}),l=Bn({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var jL={kernelName:Bh,backendName:"webgl",kernelFunc:Ka},s_="return (a < 0.) ? b * a : a;",i_=`
+    `}};function Bn(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 OL={kernelName:Fs,backendName:"webgl",kernelFunc:Bn};function Ka(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=Bn({inputs:{x:r},backend:n}),l=Bn({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var zL={kernelName:Vh,backendName:"webgl",kernelFunc:Ka},i_="return (a < 0.) ? b * a : a;",o_=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function GL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new wc(i_,a.shape,i.shape):new Bl(s_,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var qL={kernelName:Ms,backendName:"webgl",kernelFunc:GL},o_="return (a < 0.) ? b * a : a;",l_=`
+`;function PL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new bc(o_,a.shape,i.shape):new Bl(i_,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var LL={kernelName:Ms,backendName:"webgl",kernelFunc:PL},l_="return (a < 0.) ? b * a : a;",u_=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function XL(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new wc(l_,r.shape,a.shape):new Bl(o_,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var KL={kernelName:js,backendName:"webgl",kernelFunc:XL},u_="if (isnan(x)) return x;",ZL=`
+`;function WL(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new bc(u_,r.shape,a.shape):new Bl(l_,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var BL={kernelName:Hs,backendName:"webgl",kernelFunc:WL},c_="if (isnan(x)) return x;",VL=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,YL=`
+`,UL=`
   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 Qe({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let u=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new Ll(i.shape,t):c=new Xa(i.shape,e),o.runWebGLProgram(c,[i],l)}}function on({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,c=o;if(r&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[_,b]=w,x={dataId:_.dataId,dtype:_.dtype,shape:l.shape},N={dataId:b.dataId,dtype:b.dtype,shape:u.shape},S=new Bl(e,l.shape,u.shape);return c.runWebGLProgram(S,[x,N],cr(_.dtype,b.dtype))}),g=Ka({inputs:{real:A,imag:y},backend:c});return c.disposeIntermediateTensorInfo(A),c.disposeIntermediateTensorInfo(y),g}let h=s||cr(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&a!=null){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=a(l.shape,u.shape,f.values,m.values,h),g=c.makeTensorInfo(y,h),w=c.texData.get(g.dataId);return w.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new wc(t,l.shape,u.shape,n):p=new Bl(e,l.shape,u.shape),c.runWebGLProgram(p,[l,u],h)}}function Ip(e,t=!1){if(e==="linear")return t?CL:NL;if(e==="relu")return t?FL:TL;if(e==="elu")return t?RL:SL;if(e==="relu6")return t?ML:EL;if(e==="prelu")return t?l_:o_;if(e==="leakyrelu")return t?i_:s_;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var c_=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let u=r?e[1]:e[2],c=Math.ceil(u/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
+`;function Qe({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let u=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new Ll(i.shape,t):c=new Xa(i.shape,e),o.runWebGLProgram(c,[i],l)}}function on({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,c=o;if(r&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[b,_]=w,x={dataId:b.dataId,dtype:b.dtype,shape:l.shape},N={dataId:_.dataId,dtype:_.dtype,shape:u.shape},T=new Bl(e,l.shape,u.shape);return c.runWebGLProgram(T,[x,N],cr(b.dtype,_.dtype))}),g=Ka({inputs:{real:A,imag:y},backend:c});return c.disposeIntermediateTensorInfo(A),c.disposeIntermediateTensorInfo(y),g}let h=s||cr(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&a!=null){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=a(l.shape,u.shape,f.values,m.values,h),g=c.makeTensorInfo(y,h),w=c.texData.get(g.dataId);return w.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new bc(t,l.shape,u.shape,n):p=new Bl(e,l.shape,u.shape),c.runWebGLProgram(p,[l,u],h)}}function Np(e,t=!1){if(e==="linear")return t?_L:gL;if(e==="relu")return t?kL:wL;if(e==="elu")return t?vL:xL;if(e==="relu6")return t?IL:bL;if(e==="prelu")return t?u_:l_;if(e==="leakyrelu")return t?o_:i_;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var h_=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let u=r?e[1]:e[2],c=Math.ceil(u/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${i}
         }`:l?m=`vec4 activation(vec4 a) {
@@ -1042,7 +1042,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}},h_={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},d_=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
+    `}},d_={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},p_=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
       float binaryOpComplex(
           float areal, float aimag, float breal, float bimag) {
         ${e}
@@ -1055,7 +1055,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float bimag = getBImagAtOutCoords();
         setOutput(binaryOpComplex(areal, aimag, breal, bimag));
       }
-    `}},p_="return a * b;";function f_(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),u=new d_(h_.REAL,r.shape,a.shape),c=new d_(h_.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Ka({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[u,c]=aL(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(c,s),d=n.texData.get(h.dataId);return d.values=u,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new wc(p_,r.shape,a.shape):i=new Bl(p_,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var JL={kernelName:Bs,backendName:"webgl",kernelFunc:f_};function QL(e,t,n){let r=[Ii(e.shape),...Ni(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[Ii(t),...Ni(t)],i=new Yb(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function we(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let c=i.texData.get(a.dataId);return c.isPacked&&!mc(a.shape,l)&&!(c.texture!==null&&mc(c.shape,l))?QL(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var eW={kernelName:jo,backendName:"webgl",kernelFunc:we},m_=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${v.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";a%n>0&&(u=`
+    `}},f_="return a * b;";function m_(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),u=new p_(d_.REAL,r.shape,a.shape),c=new p_(d_.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Ka({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[u,c]=ZP(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(c,s),d=n.texData.get(h.dataId);return d.values=u,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new bc(f_,r.shape,a.shape):i=new Bl(f_,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var jL={kernelName:Bs,backendName:"webgl",kernelFunc:m_};function HL(e,t,n){let r=[Ii(e.shape),...Ni(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[Ii(t),...Ni(t)],i=new Jb(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function we(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let c=i.texData.get(a.dataId);return c.isPacked&&!Ac(a.shape,l)&&!(c.texture!==null&&Ac(c.shape,l))?HL(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var GL={kernelName:Ho,backendName:"webgl",kernelFunc:we},A_=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${v.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";a%n>0&&(u=`
         if (inIdx < 0 || inIdx >= ${a}) {
           return 0.0;
         }
@@ -1108,7 +1108,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(sumValue);
       }
-    `}},tW=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(n/4)*4,c=n%4,h=`
+    `}},qL=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(n/4)*4,c=n%4,h=`
       if (${t==="sum"}) {
         sumValue += dot(values, ones);
       } else if (${t==="prod"}) {
@@ -1193,12 +1193,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(${l});
       }
-    `}};function nW(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=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function Ci(e,t,n,r){let a=nW(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:u}=a[i],c,h;n==="mean"?c=i===0?new m_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new m_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):c=new tW({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},n),h=s,s=r.runWebGLProgram(c,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var aW=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=pt(this.rank),a=rW(t);this.userCode=`
+    `}};function XL(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=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function Ci(e,t,n,r){let a=XL(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:u}=a[i],c,h;n==="mean"?c=i===0?new A_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new A_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):c=new qL({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},n),h=s,s=r.runWebGLProgram(c,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var ZL=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=dt(this.rank),a=KL(t);this.userCode=`
     void main() {
       ${r} resRC = getOutputCoords();
       setOutput(getA(${a}));
     }
-    `}};function rW(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var sW=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 ${this.rank} is not yet supported.`);let r=pt(this.rank),a=Zb("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=a[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
+    `}};function KL(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var YL=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 ${this.rank} is not yet supported.`);let r=dt(this.rank),a=Yb("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=a[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
     void main() {
       ${r} rc = getOutputCoords();
       vec4 result = vec4(0.);
@@ -1215,14 +1215,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       }
       setOutput(result);
     }
-    `}};function Np(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new sW(e.shape,t):new aW(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function iW(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),u=l!=null,c=e;u&&(c=Np(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(c.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=we({inputs:{x:c},attrs:{shape:[m,f]},backend:r}),y=gd(e.dtype),g=Ci(A,y,"sum",r),w=we({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),u&&r.disposeIntermediateTensorInfo(c),w}function xA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return iW(a,s,i,n)}var oW={kernelName:ti,backendName:"webgl",kernelFunc:xA};function Cn(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let c=0;c<l.length;c++)l[c]=a.shape[s[c]];let u;if(i.shouldExecuteOnCPU([a])){let c=i.texData.get(a.dataId).values,h=yA(c,a.shape,a.dtype,s,l);u=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(u.dataId);d.values=h}else u=Np(a,s,i);return u}var lW={kernelName:ii,backendName:"webgl",kernelFunc:Cn},A_=1e3;function Sp({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,h=n?e.shape[u-2]:e.shape[u-1],d=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),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(u>=2&&c>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let _=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let b=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],N=we({inputs:{x:e},backend:a,attrs:{shape:b}}),S=we({inputs:{x:t},backend:a,attrs:{shape:x}}),T=[N,S],M=Math.max(y,g),D=n?N.shape[1]:N.shape[2],z=s!=null,B=i!=null,U=l==="leakyrelu",H=l!=null?Ip(l,!0):null,X=z||B||U||H!=null,j;if((p===1||f===1)&&D>A_&&X===!1){let Y=N,se=S;n&&(Y=Cn({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),T.push(Y)),r&&(se=Cn({inputs:{x:S},backend:a,attrs:{perm:[0,2,1]}}),T.push(se));let ne=f!==1,oe=f===1,Q=Y;ne&&(Q=we({inputs:{x:Y},backend:a,attrs:{shape:[M,D,1]}}),T.push(Q));let pe=f===1?2:1,ue=se;oe&&(ue=we({inputs:{x:se},backend:a,attrs:{shape:[M,1,D]}}),T.push(ue));let ye=f_({inputs:{a:Q,b:ue},backend:a});j=xA({inputs:{x:ye},backend:a,attrs:{axis:pe,keepDims:!0}}),T.push(ye)}else{let Y=cr(e.dtype,t.dtype),se=new c_(b,x,[M,p,f],n,r,z,H,B,U),ne=[N,S];if(s!=null&&ne.push(s),B&&ne.push(i),U){let oe=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));ne.push(oe),T.push(oe)}j=a.runWebGLProgram(se,ne,Y)}let ee=we({inputs:{x:j},backend:a,attrs:{shape:_}});T.push(j);for(let Y of T)a.disposeIntermediateTensorInfo(Y);return ee}function uW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:h}=r;return Sp({a,b:s,transposeA:l,transposeB:u,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:c})}var cW={kernelName:oi,backendName:"webgl",kernelFunc:uW},y_="return abs(x);";function hW(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=Kb(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Ll(r.shape,y_):a=new Xa(r.shape,y_),n.runWebGLProgram(a,[r],r.dtype)}var dW={kernelName:io,backendName:"webgl",kernelFunc:hW},pW=Nr+`
+    `}};function Sp(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new YL(e.shape,t):new ZL(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function JL(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),u=l!=null,c=e;u&&(c=Sp(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(c.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=we({inputs:{x:c},attrs:{shape:[m,f]},backend:r}),y=xd(e.dtype),g=Ci(A,y,"sum",r),w=we({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),u&&r.disposeIntermediateTensorInfo(c),w}function xA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return JL(a,s,i,n)}var QL={kernelName:ti,backendName:"webgl",kernelFunc:xA};function Cn(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let c=0;c<l.length;c++)l[c]=a.shape[s[c]];let u;if(i.shouldExecuteOnCPU([a])){let c=i.texData.get(a.dataId).values,h=yA(c,a.shape,a.dtype,s,l);u=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(u.dataId);d.values=h}else u=Sp(a,s,i);return u}var eW={kernelName:ii,backendName:"webgl",kernelFunc:Cn},y_=1e3;function Tp({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,h=n?e.shape[u-2]:e.shape[u-1],d=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),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(u>=2&&c>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let b=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],N=we({inputs:{x:e},backend:a,attrs:{shape:_}}),T=we({inputs:{x:t},backend:a,attrs:{shape:x}}),E=[N,T],M=Math.max(y,g),z=n?N.shape[1]:N.shape[2],B=s!=null,V=i!=null,U=l==="leakyrelu",j=l!=null?Np(l,!0):null,X=B||V||U||j!=null,G;if((p===1||f===1)&&z>y_&&X===!1){let Y=N,se=T;n&&(Y=Cn({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),E.push(Y)),r&&(se=Cn({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),E.push(se));let ne=f!==1,le=f===1,Q=Y;ne&&(Q=we({inputs:{x:Y},backend:a,attrs:{shape:[M,z,1]}}),E.push(Q));let pe=f===1?2:1,ue=se;le&&(ue=we({inputs:{x:se},backend:a,attrs:{shape:[M,1,z]}}),E.push(ue));let ye=m_({inputs:{a:Q,b:ue},backend:a});G=xA({inputs:{x:ye},backend:a,attrs:{axis:pe,keepDims:!0}}),E.push(ye)}else{let Y=cr(e.dtype,t.dtype),se=new h_(_,x,[M,p,f],n,r,B,j,V,U),ne=[N,T];if(s!=null&&ne.push(s),V&&ne.push(i),U){let le=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));ne.push(le),E.push(le)}G=a.runWebGLProgram(se,ne,Y)}let ee=we({inputs:{x:G},backend:a,attrs:{shape:b}});E.push(G);for(let Y of E)a.disposeIntermediateTensorInfo(Y);return ee}function tW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:h}=r;return Tp({a,b:s,transposeA:l,transposeB:u,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:c})}var nW={kernelName:oi,backendName:"webgl",kernelFunc:tW},g_="return abs(x);";function rW(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=Zb(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Ll(r.shape,g_):a=new Xa(r.shape,g_),n.runWebGLProgram(a,[r],r.dtype)}var aW={kernelName:io,backendName:"webgl",kernelFunc:rW},sW=Nr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return acos(x);
-`,fW=Qe({opSnippet:pW}),mW={kernelName:oo,backendName:"webgl",kernelFunc:fW},AW=Nr+`
+`,iW=Qe({opSnippet:sW}),oW={kernelName:oo,backendName:"webgl",kernelFunc:iW},lW=Nr+`
   if (x < 1.0) return NAN;
-return log(x + sqrt(x * x - 1.0));`,yW=Qe({opSnippet:AW}),gW={kernelName:lo,backendName:"webgl",kernelFunc:yW},g_="return a + b;",xW=on({opSnippet:g_,packedOpSnippet:g_,supportsComplex:!0,cpuKernelImpl:UP}),wW={kernelName:Fa,backendName:"webgl",kernelFunc:xW},bW=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+return log(x + sqrt(x * x - 1.0));`,uW=Qe({opSnippet:lW}),cW={kernelName:lo,backendName:"webgl",kernelFunc:uW},x_="return a + b;",hW=on({opSnippet:x_,packedOpSnippet:x_,supportsComplex:!0,cpuKernelImpl:DP}),dW={kernelName:Fa,backendName:"webgl",kernelFunc:hW},pW=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1230,7 +1230,7 @@ return log(x + sqrt(x * x - 1.0));`,yW=Qe({opSnippet:AW}),gW={kernelName:lo,back
         float result = ${r};
         setOutput(result);
       }
-    `}},_W=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+    `}},fW=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1238,7 +1238,7 @@ return log(x + sqrt(x * x - 1.0));`,yW=Qe({opSnippet:AW}),gW={kernelName:lo,back
         vec4 result = ${r};
         setOutput(result);
       }
-    `}};function Tp(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return Bn({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=Tp({inputs:r.slice(0,o),backend:n}),u=Tp({inputs:r.slice(o),backend:n});return Tp({inputs:[l,u],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>cr(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new _W(r[0].shape,s):new bW(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var vW={kernelName:ms,backendName:"webgl",kernelFunc:Tp};function kW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("all",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=we({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=Ci(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=we({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=we({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var IW={kernelName:Oh,backendName:"webgl",kernelFunc:kW};function NW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("any",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=we({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=Ci(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=we({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=we({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var SW={kernelName:zh,backendName:"webgl",kernelFunc:NW},TW=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
+    `}};function Ep(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return Bn({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=Ep({inputs:r.slice(0,o),backend:n}),u=Ep({inputs:r.slice(o),backend:n});return Ep({inputs:[l,u],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>cr(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new fW(r[0].shape,s):new pW(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var mW={kernelName:ms,backendName:"webgl",kernelFunc:Ep};function AW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("all",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=we({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=Ci(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=we({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=we({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var yW={kernelName:zh,backendName:"webgl",kernelFunc:AW};function gW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("any",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=we({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=Ci(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=we({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=we({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var xW={kernelName:Ph,backendName:"webgl",kernelFunc:gW},wW=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
@@ -1258,7 +1258,7 @@ return log(x + sqrt(x * x - 1.0));`,yW=Qe({opSnippet:AW}),gW={kernelName:lo,back
         }
         setOutput(float(bestIndex));
       }
-    `}},EW=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=pt(o),u=xn("coords",o),c,h;if(s===1){h=o+1;let N=pt(h);c=`
+    `}},bW=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=dt(o),u=xn("coords",o),c,h;if(s===1){h=o+1;let N=dt(h);c=`
         ${N} sourceLocR = ${N}(${u.join()}, 0);
         ++${u[o-1]};
         ${N} sourceLocG = ${N}(${u.join()}, 0);
@@ -1274,11 +1274,11 @@ return log(x + sqrt(x * x - 1.0));`,yW=Qe({opSnippet:AW}),gW={kernelName:lo,back
         ${l} sourceLocA = coords;
         --${u[o-1]};
         ${l} sourceLocB = coords;
-        --${u[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=xn("sourceLocR",h-1).concat("inIdx.r"),A=xn("sourceLocG",h-1).concat("inIdx.g"),y=xn("sourceLocB",h-1).concat("inIdx.b"),g=xn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",_=r?"":`
+        --${u[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=xn("sourceLocR",h-1).concat("inIdx.r"),A=xn("sourceLocG",h-1).concat("inIdx.g"),y=xn("sourceLocB",h-1).concat("inIdx.b"),g=xn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",b=r?"":`
           inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
                              getBestIndicesAChannel(${A.join()}),
                              getBestIndicesAChannel(${y.join()}),
-                             getBestIndicesAChannel(${g.join()})));`,b=`vec4(
+                             getBestIndicesAChannel(${g.join()})));`,_=`vec4(
             getAChannel(${m.join()}),
             hasNextCol ? getAChannel(${A.join()}) : 0.,
             hasNextRow ? getAChannel(${y.join()}) : 0.,
@@ -1301,12 +1301,12 @@ return log(x + sqrt(x * x - 1.0));`,yW=Qe({opSnippet:AW}),gW={kernelName:lo,back
           sourceLocB${p}, sourceLocA${p}) * ${t};
         ivec4 inIdx = srcIdx;
         vec4 bestIndex = vec4(inIdx);
-        vec4 bestValue = ${b};
+        vec4 bestValue = ${_};
 
         for (int i = 0; i < ${t}; i++) {
           inIdx = srcIdx;
-          ${_}
-          vec4 candidate = ${b};
+          ${b}
+          vec4 candidate = ${_};
           bvec4 nan = isnan(candidate);
           bvec4 replace = bvec4(
             vec4(${w}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
@@ -1320,23 +1320,23 @@ return log(x + sqrt(x * x - 1.0));`,yW=Qe({opSnippet:AW}),gW={kernelName:lo,back
         }
         setOutput(bestIndex);
       }
-    `}};function x_(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new TW(o,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 h=x_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),h}function w_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new EW(a,i,n,r==null),l=r==null?[t]:[t,r],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let c=w_(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function b_(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),u=we({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(u);let c=x_(e,u,r);s.push(c);let h=we({inputs:{x:c},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return w_(e,t,r)}function CW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Cn({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let c=b_(n,l,i[0],"max");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var RW={kernelName:As,backendName:"webgl",kernelFunc:CW};function FW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Cn({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let c=b_(n,l,i[0],"min");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var MW={kernelName:gu,backendName:"webgl",kernelFunc:FW},$W=Nr+`
+    `}};function w_(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new wW(o,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 h=w_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),h}function b_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new bW(a,i,n,r==null),l=r==null?[t]:[t,r],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let c=b_(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function __(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),u=we({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(u);let c=w_(e,u,r);s.push(c);let h=we({inputs:{x:c},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return b_(e,t,r)}function _W(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Cn({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let c=__(n,l,i[0],"max");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var vW={kernelName:As,backendName:"webgl",kernelFunc:_W};function kW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Cn({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let c=__(n,l,i[0],"min");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var IW={kernelName:xu,backendName:"webgl",kernelFunc:kW},NW=Nr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return asin(x);
-`,DW=Qe({opSnippet:$W}),OW={kernelName:uo,backendName:"webgl",kernelFunc:DW},zW=Nr+"return log(x + sqrt(x * x + 1.0));",PW=Qe({opSnippet:zW}),LW={kernelName:co,backendName:"webgl",kernelFunc:PW},WW=Nr+`
+`,SW=Qe({opSnippet:NW}),TW={kernelName:uo,backendName:"webgl",kernelFunc:SW},EW=Nr+"return log(x + sqrt(x * x + 1.0));",CW=Qe({opSnippet:EW}),RW={kernelName:co,backendName:"webgl",kernelFunc:CW},FW=Nr+`
   return atan(x);
-`,BW=Qe({opSnippet:WW}),VW={kernelName:ho,backendName:"webgl",kernelFunc:BW},UW=ZL+`
+`,MW=Qe({opSnippet:FW}),$W={kernelName:ho,backendName:"webgl",kernelFunc:MW},DW=VL+`
   return atan(a, b);
-`,HW=`
+`,OW=`
   vec4 result = atan(a, b);
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+YL+`
+  `+UL+`
   return result;
-`,jW=on({opSnippet:UW,packedOpSnippet:HW}),GW={kernelName:fo,backendName:"webgl",kernelFunc:jW},qW=Nr+`
+`,zW=on({opSnippet:DW,packedOpSnippet:OW}),PW={kernelName:fo,backendName:"webgl",kernelFunc:zW},LW=Nr+`
   if ((x < -1.0) || (x > 1.0)) return NAN;
-return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelName:po,backendName:"webgl",kernelFunc:XW},bc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=`
+return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,WW=Qe({opSnippet:LW}),BW={kernelName:po,backendName:"webgl",kernelFunc:WW},_c=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=`
         const ivec2 strides = ivec2(${i}, ${o});
         const ivec2 pads = ivec2(${d}, ${p});
 
@@ -1387,7 +1387,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let g="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let _=Math.floor(s/4)*4,b=s%4,x=`
+      `;return}let g="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let b=Math.floor(s/4)*4,_=s%4,x=`
       if (${f}) {
         avgValue += dot(values, ones);
       } else {
@@ -1432,7 +1432,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
             continue;
           }
 
-          for (int wC = 0; wC < ${_}; wC += 4) {
+          for (int wC = 0; wC < ${b}; wC += 4) {
             int xC = xCCorner + wC * ${u};
 
             vec4 values = vec4(
@@ -1445,8 +1445,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
             ${x}
           }
 
-          int xC = xCCorner + ${_};
-          if (${b===1}) {
+          int xC = xCCorner + ${b};
+          if (${_===1}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
               initializationValue,
@@ -1455,7 +1455,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
             );
 
             ${x}
-          } else if (${b===2}) {
+          } else if (${_===2}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
               getValue(batch, xR, xC + ${u}, d),
@@ -1464,7 +1464,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
             );
 
             ${x}
-          } else if (${b===3}) {
+          } else if (${_===3}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
               getValue(batch, xR, xC + ${u}, d),
@@ -1477,7 +1477,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(${w});
       }
-    `}},wA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,c=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let T=">=";this.userCode=`
+    `}},wA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,c=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let E=">=";this.userCode=`
         const ivec3 strides =
             ivec3(${i}, ${o}, ${l});
         const ivec3 pads = ivec3(${m}, ${A}, ${y});
@@ -1528,7 +1528,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
                 // use the current value.
                 float currMinMaxValue = mix(
                     value, minMaxValue, minMaxValueFound);
-                if (value ${T} currMinMaxValue) {
+                if (value ${E} currMinMaxValue) {
                   minMaxValue = value;
                   minMaxValueFound = 1.0;
                   minMaxPosition = ${r?a?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${p} * ${f} +
@@ -1539,11 +1539,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let _="max",b=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(b="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,S=`
+      `;return}let b="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,T=`
       if (${g}) {
         avgValue += dot(values, ones);
       } else {
-        minMaxValue = ${_}(values, minMaxValue);
+        minMaxValue = ${b}(values, minMaxValue);
       }
     `;this.userCode=`
       const ivec3 strides =
@@ -1604,7 +1604,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
                 getValue(batch, xD, xR, xC + 3 * ${h}, ch)
               );
 
-              ${S}
+              ${T}
             }
 
             int xC = xCCorner + ${x};
@@ -1616,7 +1616,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
                 initializationValue
               );
 
-              ${S}
+              ${T}
             } else if (${N===2}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
@@ -1625,7 +1625,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
                 initializationValue
               );
 
-              ${S}
+              ${T}
             } else if (${N===3}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
@@ -1634,13 +1634,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
                 initializationValue
               );
 
-              ${S}
+              ${T}
             }
           }
-          setOutput(${b});
+          setOutput(${_});
         }
       }
-    `}};function ZW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;Ml(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Bn({inputs:{x:a},backend:n});let h=new bc(c,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var YW={kernelName:ys,backendName:"webgl",kernelFunc:ZW};function JW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,l,u),d=new wA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var QW={kernelName:xu,backendName:"webgl",kernelFunc:JW},eB=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,c=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
+    `}};function VW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;Ml(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Bn({inputs:{x:a},backend:n});let h=new _c(c,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var UW={kernelName:ys,backendName:"webgl",kernelFunc:VW};function jW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,l,u),d=new wA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var HW={kernelName:wu,backendName:"webgl",kernelFunc:jW},GW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,c=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
       const ivec2 pads = ivec2(${u}, ${c});
       const float avgMultiplier = float(${h});
 
@@ -1682,7 +1682,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},tB=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=c-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
+    `}},qW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=c-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
       const ivec3 pads = ivec3(${p}, ${f}, ${m});
       const float avgMultiplier = float(${A});
 
@@ -1738,7 +1738,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function nB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new tB(d);return n.runWebGLProgram(p,[a],i.dtype)}var rB={kernelName:Lh,backendName:"webgl",kernelFunc:nB};function aB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;Ml([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=r,c=R.computePool2DInfo(i.shape,o,l,1,u),h=new eB(c);return n.runWebGLProgram(h,[a],i.dtype)}var sB={kernelName:Ph,backendName:"webgl",kernelFunc:aB};function iB(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return Sp({a,b:s,transposeA:i,transposeB:o,backend:n})}var oB={kernelName:gs,backendName:"webgl",kernelFunc:iB},lB=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};function XW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new qW(d);return n.runWebGLProgram(p,[a],i.dtype)}var KW={kernelName:Wh,backendName:"webgl",kernelFunc:XW};function ZW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;Ml([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=r,c=R.computePool2DInfo(i.shape,o,l,1,u),h=new GW(c);return n.runWebGLProgram(h,[a],i.dtype)}var YW={kernelName:Lh,backendName:"webgl",kernelFunc:ZW};function JW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return Tp({a,b:s,transposeA:i,transposeB:o,backend:n})}var QW={kernelName:gs,backendName:"webgl",kernelFunc:JW},eB=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         float x = getXAtOutCoords();
         float mean = getMeanAtOutCoords();
@@ -1748,7 +1748,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         float inv = scale * inversesqrt(variance + float(${s}));
         setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
       }
-    `}},uB=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}},tB=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         vec4 offset = ${i};
         vec4 scale = ${o};
@@ -1761,7 +1761,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
 
         setOutput((x - mean) * inv + offset);
       }
-    `}},cB=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[r,a,s],c=null;i!=null&&(c=i.shape,u.push(i));let h=null;o!=null&&(h=o.shape,u.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new uB(r.shape,a.shape,s.shape,c,h,l):new lB(r.shape,a.shape,s.shape,c,h,l);return t.runWebGLProgram(d,u,u[0].dtype)},hB={kernelName:Cs,backendName:"webgl",kernelFunc:cB},pB=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=pt(this.rank),n=`uniform int start[${this.rank}];`,r=dB(this.rank),a,s=e.map((i,o)=>`sourceLoc.${bA[o]} = start[${o}] + coords.${bA[o]};`);a=`
+    `}},nB=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[r,a,s],c=null;i!=null&&(c=i.shape,u.push(i));let h=null;o!=null&&(h=o.shape,u.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new tB(r.shape,a.shape,s.shape,c,h,l):new eB(r.shape,a.shape,s.shape,c,h,l);return t.runWebGLProgram(d,u,u[0].dtype)},rB={kernelName:Cs,backendName:"webgl",kernelFunc:nB},sB=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=dt(this.rank),n=`uniform int start[${this.rank}];`,r=aB(this.rank),a,s=e.map((i,o)=>`sourceLoc.${bA[o]} = start[${o}] + coords.${bA[o]};`);a=`
         ${t} sourceLoc;
         ${t} coords = getOutputCoords();
         ${s.join(`
@@ -1772,7 +1772,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         ${a}
         setOutput(getSource(${r}));
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},bA=["x","y","z","w","u","v"];function dB(e){if(e===1)return"sourceLoc";if(e<=6)return bA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var fB=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=pt(this.rank),n=xn("coords",this.rank),r=xn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${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)}}},bA=["x","y","z","w","u","v"];function aB(e){if(e===1)return"sourceLoc";if(e<=6)return bA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var iB=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=dt(this.rank),n=xn("coords",this.rank),r=xn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
       result.x = ${s};
       if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
         ++${r[this.rank-1]};
@@ -1802,7 +1802,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         ${o}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function mB(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=fn.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function _c(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=fn.parseSliceParams(a,s,i);if(fn.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=uL(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:u}=n.texData.get(a.dataId),c=fn.isSliceContinous(a.shape,o,l);if(u||!c){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new fB(l):new pB(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),mB(a,o,l,n)}var AB={kernelName:Ko,backendName:"webgl",kernelFunc:_c},yB=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=R.getReshaped(a.shape,s,o),u=R.getPermuted(l.length,s.length),c=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(c,i,s.length),p=[],f=we({inputs:{x:a},backend:n,attrs:{shape:l}}),m=Cn({inputs:{x:f},backend:n,attrs:{perm:u}}),A=we({inputs:{x:m},backend:n,attrs:{shape:c}}),y=_c({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},gB={kernelName:wu,backendName:"webgl",kernelFunc:yB};function xB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),u=Xb(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var wB={kernelName:Wh,backendName:"webgl",kernelFunc:xB},bB="return float(a != b);",__=on({opSnippet:bB,dtype:"bool"}),_B={kernelName:zo,backendName:"webgl",kernelFunc:__};function vc(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return Bn({inputs:{x:a.complexTensorInfos.real},backend:n})}var vB={kernelName:od,backendName:"webgl",kernelFunc:vc},kB="return float(int(x));";function IB(e,t){let n=new Xa(e.shape,kB),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function _A(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return Bn({inputs:{x:a},backend:n});let i=Ot(a.shape),o=_A({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Ka({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=vc({inputs:{input:a},backend:n}),o=_A({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=Bn({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return IB(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=__({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var NB={kernelName:xs,backendName:"webgl",kernelFunc:_A},v_="return ceil(x);",SB=Qe({opSnippet:v_,packedOpSnippet:v_,cpuKernelImpl:jP}),TB={kernelName:ws,backendName:"webgl",kernelFunc:SB},EB=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${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 oB(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=fn.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function vc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=fn.parseSliceParams(a,s,i);if(fn.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=tL(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:u}=n.texData.get(a.dataId),c=fn.isSliceContinous(a.shape,o,l);if(u||!c){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new iB(l):new sB(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),oB(a,o,l,n)}var lB={kernelName:Ko,backendName:"webgl",kernelFunc:vc},uB=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=R.getReshaped(a.shape,s,o),u=R.getPermuted(l.length,s.length),c=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(c,i,s.length),p=[],f=we({inputs:{x:a},backend:n,attrs:{shape:l}}),m=Cn({inputs:{x:f},backend:n,attrs:{perm:u}}),A=we({inputs:{x:m},backend:n,attrs:{shape:c}}),y=vc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},cB={kernelName:bu,backendName:"webgl",kernelFunc:uB};function hB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),u=Kb(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var dB={kernelName:Bh,backendName:"webgl",kernelFunc:hB},pB="return float(a != b);",v_=on({opSnippet:pB,dtype:"bool"}),fB={kernelName:zo,backendName:"webgl",kernelFunc:v_};function kc(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return Bn({inputs:{x:a.complexTensorInfos.real},backend:n})}var mB={kernelName:ld,backendName:"webgl",kernelFunc:kc},AB="return float(int(x));";function yB(e,t){let n=new Xa(e.shape,AB),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function _A(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return Bn({inputs:{x:a},backend:n});let i=Ot(a.shape),o=_A({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Ka({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=kc({inputs:{input:a},backend:n}),o=_A({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=Bn({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return yB(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=v_({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var gB={kernelName:xs,backendName:"webgl",kernelFunc:_A},k_="return ceil(x);",xB=Qe({opSnippet:k_,packedOpSnippet:k_,cpuKernelImpl:zP}),wB={kernelName:ws,backendName:"webgl",kernelFunc:xB},bB=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1815,7 +1815,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
 
         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)}}},CB=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
+    `}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)}}},_B=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1829,7 +1829,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
 
         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 RB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new CB(a.shape):o=new EB(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var FB={kernelName:Ma,backendName:"webgl",kernelFunc:RB},MB=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
+    `}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 vB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new _B(a.shape):o=new bB(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var kB={kernelName:Ma,backendName:"webgl",kernelFunc:vB},IB=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
       void main() {
         float re = abs(getRealAtOutCoords());
         float im = abs(getImagAtOutCoords());
@@ -1842,7 +1842,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
           mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
         );
       }
-    `}};function k_(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function $B(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new MB(r.shape),i=[k_(r,a.complexTensorInfos.real),k_(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var DB={kernelName:bu,backendName:"webgl",kernelFunc:$B},OB=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
+    `}};function I_(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function NB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new IB(r.shape),i=[I_(r,a.complexTensorInfos.real),I_(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var SB={kernelName:_u,backendName:"webgl",kernelFunc:NB},TB=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int yR = coords.x;
@@ -1851,18 +1851,18 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         ${n.join(`
         `)}
       }
-    `}},zB=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=pt(r),s=xn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],u=i.slice(-2),c=i.join(),h=`if (${l} < ${o[0]}) {
+    `}},EB=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=dt(r),s=xn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],u=i.slice(-2),c=i.join(),h=`if (${l} < ${o[0]}) {
         return getChannel(
             getT0(${c}), vec2(${u.join()}));
         }`;for(let f=1;f<o.length;f++){let m=o[f-1];h+=`
         if (${l} < ${o[f]}  && ${l} >= ${o[f-1]}) {
           return getChannel(
-            getT${f}(${Ep(i,l,m)}),
-            vec2(${Ep(u,l,m)}));
+            getT${f}(${Cp(i,l,m)}),
+            vec2(${Cp(u,l,m)}));
         }`}let d=o.length,p=o[o.length-1];h+=`
         return getChannel(
-          getT${d}(${Ep(i,l,p)}),
-          vec2(${Ep(u,l,p)}));`,this.userCode=`
+          getT${d}(${Cp(i,l,p)}),
+          vec2(${Cp(u,l,p)}));`,this.userCode=`
       float getValue(${i.map(f=>"int "+f)}) {
         ${h}
       }
@@ -1888,7 +1888,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(result);
       }
-    `}};function Ep(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function Cp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return Bn({inputs:{x:a.complexTensorInfos.imag},backend:n})}var PB={kernelName:ed,backendName:"webgl",kernelFunc:Cp};function Vl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let u=e.map(f=>vc({inputs:{input:f},backend:n})),c=e.map(f=>Cp({inputs:{input:f},backend:n})),h=Vl(u,t,n),d=Vl(c,t,n),p=Ka({inputs:{real:h,imag:d},backend:n});return u.forEach(f=>n.disposeIntermediateTensorInfo(f)),c.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:u,outShape:c}=I_(e,t,n),h=u.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=u[0].shape[0]===1,p=GP(h,c,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return u.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(e.length/2),c=Vl(e.slice(0,u),t,n),h=Vl(e.slice(u),t,n),d=Vl([c,h],t,n);return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let u=new zB(e.map(c=>c.shape),t);return n.runWebGLProgram(u,e,r)}let{tensors2D:a,outShape:s}=I_(e,t,n),i=new OB(a.map(u=>u.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(u=>n.disposeIntermediateTensorInfo(u));let l=we({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function I_(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>we({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function N_(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(u=>v.sizeFromShape(u.shape)>0);if(o.length===1)return Bn({inputs:{x:o[0]},backend:n});let l=o.map(u=>u.shape);return R.assertParamsConsistent(l,s),Vl(o,s,n)}var LB={kernelName:mo,backendName:"webgl",kernelFunc:N_},S_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,w="",_="";n&&(r?w=`float activation(float a) {
+    `}};function Cp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function Rp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return Bn({inputs:{x:a.complexTensorInfos.imag},backend:n})}var CB={kernelName:td,backendName:"webgl",kernelFunc:Rp};function Vl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let u=e.map(f=>kc({inputs:{input:f},backend:n})),c=e.map(f=>Rp({inputs:{input:f},backend:n})),h=Vl(u,t,n),d=Vl(c,t,n),p=Ka({inputs:{real:h,imag:d},backend:n});return u.forEach(f=>n.disposeIntermediateTensorInfo(f)),c.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:u,outShape:c}=N_(e,t,n),h=u.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=u[0].shape[0]===1,p=PP(h,c,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return u.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(e.length/2),c=Vl(e.slice(0,u),t,n),h=Vl(e.slice(u),t,n),d=Vl([c,h],t,n);return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let u=new EB(e.map(c=>c.shape),t);return n.runWebGLProgram(u,e,r)}let{tensors2D:a,outShape:s}=N_(e,t,n),i=new TB(a.map(u=>u.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(u=>n.disposeIntermediateTensorInfo(u));let l=we({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function N_(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>we({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function S_(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(u=>v.sizeFromShape(u.shape)>0);if(o.length===1)return Bn({inputs:{x:o[0]},backend:n});let l=o.map(u=>u.shape);return R.assertParamsConsistent(l,s),Vl(o,s,n)}var RB={kernelName:mo,backendName:"webgl",kernelFunc:S_},T_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,w="",b="";n&&(r?w=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?w=`float activation(float a) {
@@ -1898,7 +1898,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
           float activation(float x) {
             ${n}
           }
-        `,_="result = activation(result);");let b=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
+        `,b="result = activation(result);");let _=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${w}
 
       const ivec2 strides = ivec2(${o}, ${l});
@@ -2018,11 +2018,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
 
         float result = dotProd;
-        ${b}
         ${_}
+        ${b}
         setOutput(result);
       }
-    `}},WB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
+    `}},FB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
       const ivec3 strides = ivec3(${a}, ${s}, ${i});
       const ivec3 pads = ivec3(${t}, ${n}, ${r});
 
@@ -2110,9 +2110,9 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},BB=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:u,dilationHeight:c,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=gn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let _=0;_<=1;_++)for(let b=0;b<=1;b++)w+=`
-          blockIndex = rc.y + ${b};
-          pos = rc.x + ${_};
+    `}},MB=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:u,dilationHeight:c,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=gn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let b=0;b<=1;b++)for(let _=0;_<=1;_++)w+=`
+          blockIndex = rc.y + ${_};
+          pos = rc.x + ${b};
 
           if(blockIndex < ${e[1]} && pos < ${e[0]}) {
             offsetY = int(blockIndex / (${l})) * ${i} - ${p};
@@ -2129,12 +2129,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
 
                 if (${A}) {
                   innerDims = vec2(d1, ch);
-                  result[${_*2+b}] = getChannel(
+                  result[${b*2+_}] = getChannel(
                     getA(d0, int(innerDims.x),
                     int(innerDims.y)), innerDims);
                 } else {
                   innerDims = vec2(d0, d1);
-                  result[${_*2+b}] = getChannel(
+                  result[${b*2+_}] = getChannel(
                     getA(ch, int(innerDims.x),
                     int(innerDims.y)), innerDims);
                 }
@@ -2154,7 +2154,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
 
         ${m.output} = result;
       }
-    `}};function T_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=r.texData.get(e.dataId),c=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&c>A_,w=l[2]%2!=0&&!!u.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let _=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],b=we({inputs:{x:e},backend:r,attrs:{shape:[1,_,n.inChannels]}}),x=we({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=Sp({a:b,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=we({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(b),y.push(x),y.push(N)}else{let _=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),b={dataId:e.dataId,shape:[1,_,n.inChannels],dtype:e.dtype},x=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(mc(u.shape,b.shape),()=>`packed reshape ${u.shape} to ${b.shape} isn't free`);let N=we({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let S=Sp({a:b,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),T=r.texData.get(S.dataId);v.assert(T.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=x,T.shape=n.outShape,A=Bn({inputs:{x:S},backend:r}),A.shape=n.outShape,y.push(S)}for(let _ of y)r.disposeIntermediateTensorInfo(_);return A}function E_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*u*c,A=d*h,y=[m,A],g=!0,w=!1,_=[],b=we({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=we({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});_.push(b),_.push(x);let N=new BB(y,b.shape,n),S=r.runWebGLProgram(N,[b],"float32"),T=we({inputs:{x:S},backend:r,attrs:{shape:[1,y[0],y[1]]}});_.push(S),_.push(T);let M=a!=null,D=s!=null,z=o==="leakyrelu",B=o?Ip(o,!0):null,U=new c_(T.shape,x.shape,[1,A,n.outChannels],g,w,M,B,D,z),H=[T,x];if(a&&H.push(a),D&&H.push(s),z){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));H.push(Y),_.push(Y)}let X=r.runWebGLProgram(U,H,"float32"),j=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=we({inputs:{x:X},backend:r,attrs:{shape:j}});_.push(X);for(let Y of _)r.disposeIntermediateTensorInfo(Y);return ee}function VB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!1,h),p;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))p=T_({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=E_({x:a,filter:s,convInfo:d,backend:n});else{let m=new S_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=we({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var UB={kernelName:bs,backendName:"webgl",kernelFunc:VB},HB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
+    `}};function E_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=r.texData.get(e.dataId),c=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&c>y_,w=l[2]%2!=0&&!!u.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=we({inputs:{x:e},backend:r,attrs:{shape:[1,b,n.inChannels]}}),x=we({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=Tp({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=we({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(N)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},x=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(Ac(u.shape,_.shape),()=>`packed reshape ${u.shape} to ${_.shape} isn't free`);let N=we({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let T=Tp({a:_,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),E=r.texData.get(T.dataId);v.assert(E.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=x,E.shape=n.outShape,A=Bn({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let b of y)r.disposeIntermediateTensorInfo(b);return A}function C_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*u*c,A=d*h,y=[m,A],g=!0,w=!1,b=[],_=we({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=we({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(_),b.push(x);let N=new MB(y,_.shape,n),T=r.runWebGLProgram(N,[_],"float32"),E=we({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});b.push(T),b.push(E);let M=a!=null,z=s!=null,B=o==="leakyrelu",V=o?Np(o,!0):null,U=new h_(E.shape,x.shape,[1,A,n.outChannels],g,w,M,V,z,B),j=[E,x];if(a&&j.push(a),z&&j.push(s),B){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));j.push(Y),b.push(Y)}let X=r.runWebGLProgram(U,j,"float32"),G=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=we({inputs:{x:X},backend:r,attrs:{shape:G}});b.push(X);for(let Y of b)r.disposeIntermediateTensorInfo(Y);return ee}function $B(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!1,h),p;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))p=E_({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=C_({x:a,filter:s,convInfo:d,backend:n});else{let m=new T_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=we({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var DB={kernelName:bs,backendName:"webgl",kernelFunc:$B},OB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2196,7 +2196,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},jB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,u=s?2:3,c=s?3:1;this.userCode=`
+    `}},zB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,u=s?2:3,c=s?3:1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
@@ -2249,7 +2249,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},GB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
+    `}},PB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
       void main() {
         ivec5 coords = getOutputCoords();
         int wF = coords.x;
@@ -2291,7 +2291,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},qB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=r-1-e.padInfo.left;this.userCode=`
+    `}},LB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=r-1-e.padInfo.left;this.userCode=`
       const ivec3 pads = ivec3(${o}, ${l}, ${u});
 
       void main() {
@@ -2348,12 +2348,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function XB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,c,i,1,o,u,!1,h),p=new HB(d);return n.runWebGLProgram(p,[a,s],"float32")}var KB={kernelName:Vh,backendName:"webgl",kernelFunc:XB};function ZB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(u),d=R.computeConv2DInfo(i,s.shape,o,1,l,c,!1,h),p=new jB(d);return n.runWebGLProgram(p,[a,s],"float32")}var YB={kernelName:_s,backendName:"webgl",kernelFunc:ZB};function JB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeConv3DInfo(a.shape,s.shape,i,l,o),c=new WB(u);return n.runWebGLProgram(c,[a,s],"float32")}var QB={kernelName:_u,backendName:"webgl",kernelFunc:JB};function eV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,u=R.computeConv3DInfo(a.shape,l,i,1,o),c=new GB(u);return n.runWebGLProgram(c,[a,s],"float32")}var tV={kernelName:Uh,backendName:"webgl",kernelFunc:eV};function nV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,u=R.computeConv3DInfo(l,s.shape,o,1,i),c=new qB(u);return n.runWebGLProgram(c,[a,s],"float32")}var rV={kernelName:Hh,backendName:"webgl",kernelFunc:nV},aV=u_+`
+    `}};function WB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,c,i,1,o,u,!1,h),p=new OB(d);return n.runWebGLProgram(p,[a,s],"float32")}var BB={kernelName:Uh,backendName:"webgl",kernelFunc:WB};function VB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(u),d=R.computeConv2DInfo(i,s.shape,o,1,l,c,!1,h),p=new zB(d);return n.runWebGLProgram(p,[a,s],"float32")}var UB={kernelName:_s,backendName:"webgl",kernelFunc:VB};function jB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeConv3DInfo(a.shape,s.shape,i,l,o),c=new FB(u);return n.runWebGLProgram(c,[a,s],"float32")}var HB={kernelName:vu,backendName:"webgl",kernelFunc:jB};function GB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,u=R.computeConv3DInfo(a.shape,l,i,1,o),c=new PB(u);return n.runWebGLProgram(c,[a,s],"float32")}var qB={kernelName:jh,backendName:"webgl",kernelFunc:GB};function XB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,u=R.computeConv3DInfo(l,s.shape,o,1,i),c=new LB(u);return n.runWebGLProgram(c,[a,s],"float32")}var KB={kernelName:Hh,backendName:"webgl",kernelFunc:XB},ZB=c_+`
   return cos(x);
-`,sV=Qe({opSnippet:aV}),iV={kernelName:vs,backendName:"webgl",kernelFunc:sV},oV=`
+`,YB=Qe({opSnippet:ZB}),JB={kernelName:vs,backendName:"webgl",kernelFunc:YB},QB=`
   float e2x = exp(-x);
   return (e2x + 1.0 / e2x) / 2.0;
-`,lV=Qe({opSnippet:oV}),uV={kernelName:Ao,backendName:"webgl",kernelFunc:lV},cV=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[c,h]=n;this.outputShape=[u,c,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=c>1?[`${(i-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,_]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
+`,eV=Qe({opSnippet:QB}),tV={kernelName:Ao,backendName:"webgl",kernelFunc:eV},nV=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[c,h]=n;this.outputShape=[u,c,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=c>1?[`${(i-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,b]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
       const float height_ratio = float(${m});
       const float width_ratio = float(${g});
       void main() {
@@ -2383,7 +2383,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
           setOutput(float(${a}));
           return;
         }
-        float in_x = ${_};
+        float in_x = ${b};
         if( in_x < 0.0 || in_x > ${f} ) {
           setOutput(float(${a}));
           return;
@@ -2414,21 +2414,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
           setOutput(newValue);
         }
       }
-    `}},hV=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=r,c=new cV(a.shape,s.shape,o,l,u);return n.runWebGLProgram(c,[a,s,i],"float32")},dV={kernelName:yo,backendName:"webgl",kernelFunc:hV},F_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${C_(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
+    `}},rV=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=r,c=new nV(a.shape,s.shape,o,l,u);return n.runWebGLProgram(c,[a,s,i],"float32")},aV={kernelName:yo,backendName:"webgl",kernelFunc:rV},M_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${R_(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
       uniform float index;
       void main() {
-        ${pt(r)} coords = getOutputCoords();
-        int end = ${R_(r,"coords")};
+        ${dt(r)} coords = getOutputCoords();
+        int end = ${F_(r,"coords")};
         float val = ${a};
         int pow2 = int(pow(2.0, index));
         if (${i}) {
           int idx = ${o};
-          ${R_(r,"coords")} = idx;
-          val += getX(${C_(r,"coords")});
+          ${F_(r,"coords")} = idx;
+          val += getX(${R_(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 C_(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 ${e} is not yet supported`)}function R_(e,t){if(e===1)return`${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 ${e} is not yet supported`)}function pV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,u=R.getAxesPermutation([s],l),c=a;u!=null&&(c=Cn({inputs:{x:a},backend:n,attrs:{perm:u}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=c.shape[h],p=Bn({inputs:{x:c},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new F_(c.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new F_(c.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(u!=null){let f=R.getUndoAxesPermutation(u),m=Cn({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(c),m}return p}var fV={kernelName:ks,backendName:"webgl",kernelFunc:pV};function mV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),u=n.readSync(s.dataId),c=Xb(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=HP(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var AV={kernelName:jh,backendName:"webgl",kernelFunc:mV},yV=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function R_(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 ${e} is not yet supported`)}function F_(e,t){if(e===1)return`${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 ${e} is not yet supported`)}function sV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,u=R.getAxesPermutation([s],l),c=a;u!=null&&(c=Cn({inputs:{x:a},backend:n,attrs:{perm:u}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=c.shape[h],p=Bn({inputs:{x:c},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new M_(c.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new M_(c.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(u!=null){let f=R.getUndoAxesPermutation(u),m=Cn({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(c),m}return p}var iV={kernelName:ks,backendName:"webgl",kernelFunc:sV};function oV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),u=n.readSync(s.dataId),c=Kb(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=OP(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var lV={kernelName:Gh,backendName:"webgl",kernelFunc:oV},uV=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];
@@ -2447,7 +2447,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
       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 gV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],c=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=u*s,p=c/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new yV(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var xV={kernelName:go,backendName:"webgl",kernelFunc:gV},M_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
+  `}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 cV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],c=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=u*s,p=c/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new uV(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var hV={kernelName:go,backendName:"webgl",kernelFunc:cV},$_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?A=`float activation(float a) {
@@ -2503,24 +2503,24 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         ${y}
         setOutput(result);
       }
-    `}},$_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let _=0;_<p;_++)for(let b=0;b<f;b++)A+=`
-          vec4 xTexelR${_}C${b*2} = vec4(0.);
-          vec4 wR${_}C${b} = vec4(0.);
-          vec4 xR${_}C${b} = vec4(0.);`;for(let _=0;_<p;_++)for(let b=0;b<m;b++){let x=b*2;if(A+=`
-          xR = xRCorner + ${_*h};
+    `}},D_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`
+          vec4 xTexelR${b}C${_*2} = vec4(0.);
+          vec4 wR${b}C${_} = vec4(0.);
+          vec4 xR${b}C${_} = vec4(0.);`;for(let b=0;b<p;b++)for(let _=0;_<m;_++){let x=_*2;if(A+=`
+          xR = xRCorner + ${b*h};
           xC = xCCorner + ${x*d};
         `,c===1){if(x<f&&(l%2==1?A+=`
                 xCOffset = xC + 1;
                 if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${_}C${x} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
 
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if(xCOffset + 1 >= ${i}) {
-                    xTexelR${_}C${x}.zw = vec2(0.);
+                    xTexelR${b}C${x}.zw = vec2(0.);
                   }
                 } else {
-                  xTexelR${_}C${x} = vec4(0.);
+                  xTexelR${b}C${x} = vec4(0.);
                 }
 
                 xCOffset = xC + 1 - 2;
@@ -2533,96 +2533,96 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
                     previous.zw = vec2(0.);
                   }
 
-                  xR${_}C${x} = vec4(previous.zw, xTexelR${_}C${x}.xy);
+                  xR${b}C${x} = vec4(previous.zw, xTexelR${b}C${x}.xy);
                 } else {
-                  xR${_}C${x} = vec4(0, 0, xTexelR${_}C${x}.xy);
+                  xR${b}C${x} = vec4(0, 0, xTexelR${b}C${x}.xy);
                 }
               `:A+=`
                 if(xR >= 0 && xR < ${s} && xC >= 0 && xC < ${i}) {
-                  xTexelR${_}C${x} = getX(batch, xR, xC, d1);
+                  xTexelR${b}C${x} = getX(batch, xR, xC, d1);
                 } else {
-                  xTexelR${_}C${x} = vec4(0.);
+                  xTexelR${b}C${x} = vec4(0.);
                 }
 
-                xR${_}C${x} = xTexelR${_}C${x};
+                xR${b}C${x} = xTexelR${b}C${x};
               `,x+1<f)){let N=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
                   xCOffset = xC + ${l%2} + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
-                    xTexelR${_}C${x+2} = getX(batch, xR, xCOffset, d1);
+                    xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
                   }
                 `,d>1&&(A+=`
                     xCOffset -= 2;
                     if(xR >= 0 && xR < ${s} &&
                       xCOffset >= 0 && xCOffset < ${i}) {
-                      xTexelR${_}C${x} = getX(batch, xR, xCOffset, d1);
+                      xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
                     } else {
-                      xTexelR${_}C${x} = vec4(0.);
+                      xTexelR${b}C${x} = vec4(0.);
                     }
                   `),A+=`
-                  xR${_}C${x+1} = vec4(
-                    xTexelR${_}C${x}.zw, xTexelR${_}C${x+2}.xy);
+                  xR${b}C${x+1} = vec4(
+                    xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.xy);
                 `):A+=`
                   xCOffset = xC + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
-                    xTexelR${_}C${x+2} = getX(batch, xR, xCOffset, d1);
+                    xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
                   }
 
-                  xR${_}C${x+1} = xTexelR${_}C${x+2};
+                  xR${b}C${x+1} = xTexelR${b}C${x+2};
                 `}}else x<f&&(A+=`
               if(xR >= 0 && xR < ${s}) {
             `,l%2==1?(A+=`
                 xCOffset = xC + 1 - ${c};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${_}C${x} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
                 } else {
-                  xTexelR${_}C${x} = vec4(0.);
+                  xTexelR${b}C${x} = vec4(0.);
                 }
 
                 if(xC + 1 >= 0 && xC + 1 < ${i}) {
-                  xTexelR${_}C${x+2} = getX(batch, xR, xC + 1, d1);
+                  xTexelR${b}C${x+2} = getX(batch, xR, xC + 1, d1);
                 } else {
-                  xTexelR${_}C${x+2} = vec4(0.);
+                  xTexelR${b}C${x+2} = vec4(0.);
                 }
 
-                xR${_}C${x} = vec4(
-                  xTexelR${_}C${x}.zw, xTexelR${_}C${x+2}.zw);
+                xR${b}C${x} = vec4(
+                  xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.zw);
               `,x+1<f&&(A+=`
                   vec4 final = vec4(0.);
                   xCOffset = xC + 1 + ${c};
                   if(xCOffset >= 0 && xCOffset < ${i}) {
                     final = getX(batch, xR, xCOffset, d1);
                   }
-                  xR${_}C${x+1} = vec4(xTexelR${_}C${x+2}.xy, final.xy);
+                  xR${b}C${x+1} = vec4(xTexelR${b}C${x+2}.xy, final.xy);
                 `)):(A+=`
                 if(xC >= 0 && xC < ${i}) {
-                  xTexelR${_}C${x} = getX(batch, xR, xC, d1);
+                  xTexelR${b}C${x} = getX(batch, xR, xC, d1);
                 } else {
-                  xTexelR${_}C${x} = vec4(0.);
+                  xTexelR${b}C${x} = vec4(0.);
                 }
 
                 xCOffset = xC + ${c};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${_}C${x+2} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
                 } else {
-                  xTexelR${_}C${x+2} = vec4(0.);
+                  xTexelR${b}C${x+2} = vec4(0.);
                 }
 
-                xR${_}C${x} = vec4(
-                  xTexelR${_}C${x}.xy, xTexelR${_}C${x+2}.xy);
+                xR${b}C${x} = vec4(
+                  xTexelR${b}C${x}.xy, xTexelR${b}C${x+2}.xy);
               `,x+1<f&&(A+=`
-                  xR${_}C${x+1} = vec4(
-                    xTexelR${_}C${x}.zw, xTexelR${_}C${x+2}.zw);
+                  xR${b}C${x+1} = vec4(
+                    xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.zw);
                 `)),A+="}");x<f&&(A+=`
-            vec4 wTexelR${_}C${x} = getW(${_}, ${x}, d1, q);
-            wR${_}C${x} = vec4(wTexelR${_}C${x}.xz, wTexelR${_}C${x}.xz);
+            vec4 wTexelR${b}C${x} = getW(${b}, ${x}, d1, q);
+            wR${b}C${x} = vec4(wTexelR${b}C${x}.xz, wTexelR${b}C${x}.xz);
           `,x+1<f&&(A+=`
-              vec4 wTexelR${_}C${x+1} = getW(${_}, ${x+1}, d1, q);
-              wR${_}C${x+1} =
-                vec4(wTexelR${_}C${x+1}.xz, wTexelR${_}C${x+1}.xz);`))}for(let _=0;_<p;_++)for(let b=0;b<f;b++)A+=`dotProd += xR${_}C${b} * wR${_}C${b};`;let y="",g="";n&&(r?y=`vec4 activation(vec4 a) {
+              vec4 wTexelR${b}C${x+1} = getW(${b}, ${x+1}, d1, q);
+              wR${b}C${x+1} =
+                vec4(wTexelR${b}C${x+1}.xz, wTexelR${b}C${x+1}.xz);`))}for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`dotProd += xR${b}C${_} * wR${b}C${_};`;let y="",g="";n&&(r?y=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?y=`vec4 activation(vec4 a) {
@@ -2656,7 +2656,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         ${g}
         setOutput(result);
       }
-    `}};function wV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=r,c=l;c==null&&(c=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new $_(h):d=new M_(h),n.runWebGLProgram(d,[a,s],"float32")}var bV={kernelName:Is,backendName:"webgl",kernelFunc:wV},_V=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
+    `}};function dV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=r,c=l;c==null&&(c=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new D_(h):d=new $_(h),n.runWebGLProgram(d,[a,s],"float32")}var pV={kernelName:Is,backendName:"webgl",kernelFunc:dV},fV=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2691,7 +2691,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},vV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
+    `}},mV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
       const ivec2 pads = ivec2(${s}, ${i});
 
       void main() {
@@ -2736,13 +2736,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function kV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:c}=r,h=R.computeConv2DInfo(a.shape,c,i,o,l,u,!0),d=new _V(h);return n.runWebGLProgram(d,[a,s],"float32")}var IV={kernelName:Gh,backendName:"webgl",kernelFunc:kV};function NV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:c}=r,h=R.computeConv2DInfo(c,s.shape,i,o,l,u,!0),d=new vV(h);return n.runWebGLProgram(d,[a,s],"float32")}var SV={kernelName:qh,backendName:"webgl",kernelFunc:NV},TV=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
+    `}};function AV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:c}=r,h=R.computeConv2DInfo(a.shape,c,i,o,l,u,!0),d=new fV(h);return n.runWebGLProgram(d,[a,s],"float32")}var yV={kernelName:qh,backendName:"webgl",kernelFunc:AV};function gV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:c}=r,h=R.computeConv2DInfo(c,s.shape,i,o,l,u,!0),d=new mV(h);return n.runWebGLProgram(d,[a,s],"float32")}var xV={kernelName:Xh,backendName:"webgl",kernelFunc:gV},wV=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 EV(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=we({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new TV(s),l=n.runWebGLProgram(o,[i],i.dtype),u=we({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var CV={kernelName:Xh,backendName:"webgl",kernelFunc:EV},RV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:c,left:h}=r;this.userCode=`
+    `}};function bV(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=we({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new wV(s),l=n.runWebGLProgram(o,[i],i.dtype),u=we({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var _V={kernelName:Kh,backendName:"webgl",kernelFunc:bV},vV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:c,left:h}=r;this.userCode=`
       const ivec2 strides = ivec2(${a}, ${s});
       const ivec2 pads = ivec2(${c}, ${h});
       const float neg_infinity = -3.4e38;
@@ -2780,7 +2780,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         float result = curVal;
         setOutput(result);
       }
-    `}};function FV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),c,h=new RV(u);c=n.runWebGLProgram(h,[a,s],"float32");let d=we({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var MV={kernelName:vu,backendName:"webgl",kernelFunc:FV},$V="return (x >= 0.0) ? x : (exp(x) - 1.0);",DV=`
+    `}};function kV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),c,h=new vV(u);c=n.runWebGLProgram(h,[a,s],"float32");let d=we({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var IV={kernelName:ku,backendName:"webgl",kernelFunc:kV},NV="return (x >= 0.0) ? x : (exp(x) - 1.0);",SV=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -2789,12 +2789,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,OV=Qe({opSnippet:$V,packedOpSnippet:DV}),zV={kernelName:xo,backendName:"webgl",kernelFunc:OV},PV="return (b >= 1.0) ? a : a * (b + 1.0);",LV=`
+`,TV=Qe({opSnippet:NV,packedOpSnippet:SV}),EV={kernelName:xo,backendName:"webgl",kernelFunc:TV},CV="return (b >= 1.0) ? a : a * (b + 1.0);",RV=`
   vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
   return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
-`,WV=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new wc(LV,r.shape,a.shape):new Bl(PV,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},BV={kernelName:Yh,backendName:"webgl",kernelFunc:WV},VV=`
+`,FV=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new bc(RV,r.shape,a.shape):new Bl(CV,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},MV={kernelName:Jh,backendName:"webgl",kernelFunc:FV},$V=`
   return vec4(equal(a, b));
-`,UV="return float(a == b);",HV=on({opSnippet:UV,packedOpSnippet:VV,dtype:"bool"}),jV={kernelName:bo,backendName:"webgl",kernelFunc:HV},GV=`
+`,DV="return float(a == b);",OV=on({opSnippet:DV,packedOpSnippet:$V,dtype:"bool"}),zV={kernelName:bo,backendName:"webgl",kernelFunc:OV},PV=`
   // Error function is calculated approximately with elementary function.
   // See "Handbook of Mathematical Functions with Formulas,
   // Graphs, and Mathematical Tables", Abramowitz and Stegun.
@@ -2809,7 +2809,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
   x = abs(x);
   float t = 1.0 / (1.0 + p * x);
   return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
-`,qV=Qe({opSnippet:GV}),XV={kernelName:wo,backendName:"webgl",kernelFunc:qV},D_="return exp(x);",O_=Qe({opSnippet:D_,packedOpSnippet:D_,cpuKernelImpl:qP}),KV={kernelName:Ss,backendName:"webgl",kernelFunc:O_};function vA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),we({inputs:{x:s},backend:r,attrs:{shape:o}})}var ZV={kernelName:_o,backendName:"webgl",kernelFunc:vA},z_="return exp(x) - 1.0;",YV=Qe({opSnippet:z_,packedOpSnippet:z_,cpuKernelImpl:XP}),JV={kernelName:vo,backendName:"webgl",kernelFunc:YV},P_=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
+`,LV=Qe({opSnippet:PV}),WV={kernelName:wo,backendName:"webgl",kernelFunc:LV},O_="return exp(x);",z_=Qe({opSnippet:O_,packedOpSnippet:O_,cpuKernelImpl:LP}),BV={kernelName:Ss,backendName:"webgl",kernelFunc:z_};function vA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),we({inputs:{x:s},backend:r,attrs:{shape:o}})}var VV={kernelName:_o,backendName:"webgl",kernelFunc:vA},P_="return exp(x) - 1.0;",UV=Qe({opSnippet:P_,packedOpSnippet:P_,cpuKernelImpl:WP}),jV={kernelName:vo,backendName:"webgl",kernelFunc:UV},L_=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
       const float exponentMultiplier = ${a};
 
       float unaryOpComplex(float real, float expR, float imag, float expI) {
@@ -2842,13 +2842,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         ivec2 coords = getOutputCoords();
         setOutput(mulMatDFT(coords[0], coords[1]));
       }
-    `}};function L_(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=we({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,u=new P_("real",l,t),c=new P_("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Ka({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=we({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function QV(e){let{inputs:t,backend:n}=e,{input:r}=t;return L_(r,!1,n)}var eU={kernelName:Jh,backendName:"webgl",kernelFunc:QV},tU=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
+    `}};function W_(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=we({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,u=new L_("real",l,t),c=new L_("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Ka({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=we({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function HV(e){let{inputs:t,backend:n}=e,{input:r}=t;return W_(r,!1,n)}var GV={kernelName:Qh,backendName:"webgl",kernelFunc:HV},qV=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 kA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new tU(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var nU={kernelName:ku,backendName:"webgl",kernelFunc:kA},rU=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function kA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new qV(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var XV={kernelName:Iu,backendName:"webgl",kernelFunc:kA},KV=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];
@@ -2862,7 +2862,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
           }
           setOutput(outputValue);
         }
-    `}},aU={kernelName:ko,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new rU(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},W_="return floor(x);",sU=Qe({opSnippet:W_,packedOpSnippet:W_,cpuKernelImpl:KP}),iU={kernelName:Ts,backendName:"webgl",kernelFunc:sU},oU=`
+    `}},ZV={kernelName:ko,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new KV(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},B_="return floor(x);",YV=Qe({opSnippet:B_,packedOpSnippet:B_,cpuKernelImpl:BP}),JV={kernelName:Ts,backendName:"webgl",kernelFunc:YV},QV=`
   float s = sign(a) * sign(b);
   int ia = round(a);
   int ib = round(b);
@@ -2872,7 +2872,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
   } else {
     return NAN;
   }
-`,lU=`
+`,eU=`
   ivec4 ia = round(a);
   ivec4 ib = round(b);
   bvec4 cond = notEqual(ib, ivec4(0));
@@ -2893,7 +2893,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
     result[3] = idiv(ia[3], ib[3], s[3]);
   }
   return vec4(result);
-`,uU=on({opSnippet:oU,packedOpSnippet:lU,dtype:"int32"}),cU={kernelName:Es,backendName:"webgl",kernelFunc:uU},hU=class{constructor(e){this.variableNames=["A"];let t=gn(),[n,r]=e;this.outputShape=e,this.userCode=`
+`,tU=on({opSnippet:QV,packedOpSnippet:eU,dtype:"int32"}),nU={kernelName:Es,backendName:"webgl",kernelFunc:tU},rU=class{constructor(e){this.variableNames=["A"];let t=gn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2915,7 +2915,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
 
         setOutput(floor(value * 255.0 + 0.5));
       }
-    `}},dU=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=gn(),[n,r]=e;this.outputShape=e,this.userCode=`
+    `}},aU=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=gn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2949,7 +2949,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
 
         ${t.output} = result;
       }
-    `}},fU={kernelName:pd,backendName:"webgl",kernelFunc:pU},Ul;function pU(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,u]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],c=[u,l],h=[u,l,s];(o||i)&&(Ul==null&&(Ul=document.createElement("canvas").getContext("2d")),Ul.canvas.width=l,Ul.canvas.height=u,Ul.drawImage(a,0,0,l,u),a=Ul.canvas);let d=n.makeTensorInfo(c,"int32");n.texData.get(d.dataId).usage=nr.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new dU(h):new hU(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function mU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(c),A=R.computeConv2DInfo(a.shape,s.shape,l,h,u,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=T_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=E_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let _=i!=null,b=o!=null,x=p==="leakyrelu",N=p?Ip(p,!1):null,S=new S_(A,_,N,b,x),T=[a,s];if(i&&T.push(i),o&&T.push(o),x){let M=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));T.push(M),g.push(M)}y=n.runWebGLProgram(S,T,"float32")}let w=we({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(_=>n.disposeIntermediateTensorInfo(_)),w}var AU={kernelName:li,backendName:"webgl",kernelFunc:mU};function yU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=c;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,u,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?Ip(d,y):null,w=[a,s],_=i!=null,b=o!=null,x=d==="leakyrelu";if(_&&w.push(i),b&&w.push(o),x){let T=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(T),f.push(T)}let N;y?N=new $_(A,_,g,b,x):N=new M_(A,_,g,b,x);let S=n.runWebGLProgram(N,w,"float32");return f.forEach(T=>n.disposeIntermediateTensorInfo(T)),S}var gU={kernelName:ui,backendName:"webgl",kernelFunc:yU},xU=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=pt(t.length),a=pt(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
+    `}},iU={kernelName:fd,backendName:"webgl",kernelFunc:sU},Ul;function sU(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,u]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],c=[u,l],h=[u,l,s];(o||i)&&(Ul==null&&(Ul=document.createElement("canvas").getContext("2d")),Ul.canvas.width=l,Ul.canvas.height=u,Ul.drawImage(a,0,0,l,u),a=Ul.canvas);let d=n.makeTensorInfo(c,"int32");n.texData.get(d.dataId).usage=nr.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new aU(h):new rU(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function oU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(c),A=R.computeConv2DInfo(a.shape,s.shape,l,h,u,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=E_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=C_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let b=i!=null,_=o!=null,x=p==="leakyrelu",N=p?Np(p,!1):null,T=new T_(A,b,N,_,x),E=[a,s];if(i&&E.push(i),o&&E.push(o),x){let M=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));E.push(M),g.push(M)}y=n.runWebGLProgram(T,E,"float32")}let w=we({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var lU={kernelName:li,backendName:"webgl",kernelFunc:oU};function uU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=c;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,u,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?Np(d,y):null,w=[a,s],b=i!=null,_=o!=null,x=d==="leakyrelu";if(b&&w.push(i),_&&w.push(o),x){let E=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(E),f.push(E)}let N;y?N=new D_(A,b,g,_,x):N=new $_(A,b,g,_,x);let T=n.runWebGLProgram(N,w,"float32");return f.forEach(E=>n.disposeIntermediateTensorInfo(E)),T}var cU={kernelName:ui,backendName:"webgl",kernelFunc:uU},hU=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=dt(t.length),a=dt(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
         ${r} strides = ${r}(${this.strides});
          void main() {
           ${a} coords = getOutputCoords();
@@ -2960,21 +2960,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
           }
           setOutput(getX(flattenIndex, coords[1]));
         }
-      `}};function wU(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,u,c]=R.prepareAndValidate(r,a),h=we({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=we({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/u,u]}}),p=new xU(i,c,[l,u]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=we({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var bU={kernelName:No,backendName:"webgl",kernelFunc:wU},vU=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=pt(this.rank),r=_U(e,2);this.userCode=`
+      `}};function dU(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,u,c]=R.prepareAndValidate(r,a),h=we({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=we({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/u,u]}}),p=new hU(i,c,[l,u]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=we({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var pU={kernelName:No,backendName:"webgl",kernelFunc:dU},mU=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=dt(this.rank),r=fU(e,2);this.userCode=`
       void main() {
         ${n} resRC = getOutputCoords();
         setOutput(getA(${r}));
       }
-    `}};function _U(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function kU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],u=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),c=v.sizeFromShape(s.shape),h=[],d=we({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),p=we({inputs:{x:s},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});h.push(d),h.push(p);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),_=ZP(w,g,f);return h.forEach(b=>n.disposeIntermediateTensorInfo(b)),n.makeTensorInfo(u.outputShape,_.dtype,_.values)}let m=new vU(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=we({inputs:{x:A},backend:n,attrs:{shape:u.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var IU={kernelName:Io,backendName:"webgl",kernelFunc:kU},NU="return float(a > b);",SU=`
+    `}};function fU(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function AU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],u=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),c=v.sizeFromShape(s.shape),h=[],d=we({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),p=we({inputs:{x:s},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});h.push(d),h.push(p);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),b=VP(w,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new mU(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=we({inputs:{x:A},backend:n,attrs:{shape:u.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var yU={kernelName:Io,backendName:"webgl",kernelFunc:AU},gU="return float(a > b);",xU=`
   return vec4(greaterThan(a, b));
-`,TU=on({opSnippet:NU,packedOpSnippet:SU,cpuKernelImpl:YP,dtype:"bool"}),EU={kernelName:So,backendName:"webgl",kernelFunc:TU},CU="return float(a >= b);",RU=`
+`,wU=on({opSnippet:gU,packedOpSnippet:xU,cpuKernelImpl:UP,dtype:"bool"}),bU={kernelName:So,backendName:"webgl",kernelFunc:wU},_U="return float(a >= b);",vU=`
   return vec4(greaterThanEqual(a, b));
-`,FU=on({opSnippet:CU,packedOpSnippet:RU,dtype:"bool"}),MU={kernelName:Rs,backendName:"webgl",kernelFunc:FU};function $U(e){let{inputs:t,backend:n}=e,{input:r}=t;return L_(r,!0,n)}var DU={kernelName:Qh,backendName:"webgl",kernelFunc:$U},OU="return float(!isnan(x) && !isinf(x));",zU=Qe({opSnippet:OU,dtype:"bool"}),PU={kernelName:To,backendName:"webgl",kernelFunc:zU},LU="return float(isinf(x));",WU=Qe({opSnippet:LU,dtype:"bool"}),BU={kernelName:Eo,backendName:"webgl",kernelFunc:WU},VU="return float(isnan(x));",UU=Qe({opSnippet:VU,dtype:"bool"}),HU={kernelName:Co,backendName:"webgl",kernelFunc:UU},jU="return float(a < b);",GU=`
+`,kU=on({opSnippet:_U,packedOpSnippet:vU,dtype:"bool"}),IU={kernelName:Rs,backendName:"webgl",kernelFunc:kU};function NU(e){let{inputs:t,backend:n}=e,{input:r}=t;return W_(r,!0,n)}var SU={kernelName:ed,backendName:"webgl",kernelFunc:NU},TU="return float(!isnan(x) && !isinf(x));",EU=Qe({opSnippet:TU,dtype:"bool"}),CU={kernelName:To,backendName:"webgl",kernelFunc:EU},RU="return float(isinf(x));",FU=Qe({opSnippet:RU,dtype:"bool"}),MU={kernelName:Eo,backendName:"webgl",kernelFunc:FU},$U="return float(isnan(x));",DU=Qe({opSnippet:$U,dtype:"bool"}),OU={kernelName:Co,backendName:"webgl",kernelFunc:DU},zU="return float(a < b);",PU=`
   return vec4(lessThan(a, b));
-`,qU=on({opSnippet:jU,packedOpSnippet:GU,cpuKernelImpl:JP,dtype:"bool"}),XU={kernelName:Ro,backendName:"webgl",kernelFunc:qU},KU="return float(a <= b);",ZU=`
+`,LU=on({opSnippet:zU,packedOpSnippet:PU,cpuKernelImpl:jP,dtype:"bool"}),WU={kernelName:Ro,backendName:"webgl",kernelFunc:LU},BU="return float(a <= b);",VU=`
   return vec4(lessThanEqual(a, b));
-`,YU=on({opSnippet:KU,packedOpSnippet:ZU,dtype:"bool"}),JU={kernelName:Fo,backendName:"webgl",kernelFunc:YU};function QU(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=QP(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var eH={kernelName:td,backendName:"webgl",kernelFunc:QU},tH=`if (x < 0.0) return NAN;
-  return log(x);`,nH=`
+`,UU=on({opSnippet:BU,packedOpSnippet:VU,dtype:"bool"}),jU={kernelName:Fo,backendName:"webgl",kernelFunc:UU};function HU(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=HP(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var GU={kernelName:nd,backendName:"webgl",kernelFunc:HU},qU=`if (x < 0.0) return NAN;
+  return log(x);`,XU=`
   vec4 result = log(x);
   vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
   result.r = isNaN.r == 1.0 ? NAN : result.r;
@@ -2983,16 +2983,16 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
   result.a = isNaN.a == 1.0 ? NAN : result.a;
 
   return result;
-`,rH=Qe({opSnippet:tH,packedOpSnippet:nH,cpuKernelImpl:eL}),aH={kernelName:$s,backendName:"webgl",kernelFunc:rH},sH="return log(1.0 + x);",iH=Qe({opSnippet:sH}),oH={kernelName:Mo,backendName:"webgl",kernelFunc:iH},lH="return float(a >= 1.0 && b >= 1.0);",uH=`
+`,KU=Qe({opSnippet:qU,packedOpSnippet:XU,cpuKernelImpl:GP}),ZU={kernelName:$s,backendName:"webgl",kernelFunc:KU},YU="return log(1.0 + x);",JU=Qe({opSnippet:YU}),QU={kernelName:Mo,backendName:"webgl",kernelFunc:JU},ej="return float(a >= 1.0 && b >= 1.0);",tj=`
   return vec4(
     vec4(greaterThanEqual(a, vec4(1.0))) *
     vec4(greaterThanEqual(b, vec4(1.0))));
-`,cH=on({opSnippet:lH,packedOpSnippet:uH,dtype:"bool"}),hH={kernelName:$o,backendName:"webgl",kernelFunc:cH},dH="return float(!(x >= 1.0));",pH=Qe({opSnippet:dH}),fH={kernelName:Iu,backendName:"webgl",kernelFunc:pH},mH="return float(a >= 1.0 || b >= 1.0);",AH=`
+`,nj=on({opSnippet:ej,packedOpSnippet:tj,dtype:"bool"}),rj={kernelName:$o,backendName:"webgl",kernelFunc:nj},aj="return float(!(x >= 1.0));",sj=Qe({opSnippet:aj}),ij={kernelName:Nu,backendName:"webgl",kernelFunc:sj},oj="return float(a >= 1.0 || b >= 1.0);",lj=`
   return min(
     vec4(greaterThanEqual(a, vec4(1.0))) +
     vec4(greaterThanEqual(b, vec4(1.0))),
     vec4(1.0));
-`,yH=on({opSnippet:mH,packedOpSnippet:AH,dtype:"bool"}),gH={kernelName:Nu,backendName:"webgl",kernelFunc:yH},xH=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+`,uj=on({opSnippet:oj,packedOpSnippet:lj,dtype:"bool"}),cj={kernelName:Su,backendName:"webgl",kernelFunc:uj},hj=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3011,7 +3011,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         float val = x * ${o};
         setOutput(val);
       }
-    `}},wH=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+    `}},dj=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords.x;
@@ -3073,7 +3073,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         vec4 result = xAtOutputCoords * ${o};
         setOutput(result);
       }
-    `}},bH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,u=J().getBool("WEBGL_PACK_NORMALIZATION")?new wH(a.shape,s,i,o,l):new xH(a.shape,s,i,o,l);return n.runWebGLProgram(u,[a],a.dtype)},_H={kernelName:Su,backendName:"webgl",kernelFunc:bH},vH=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
+    `}},pj=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,u=J().getBool("WEBGL_PACK_NORMALIZATION")?new dj(a.shape,s,i,o,l):new hj(a.shape,s,i,o,l);return n.runWebGLProgram(u,[a],a.dtype)},fj={kernelName:Tu,backendName:"webgl",kernelFunc:pj},mj=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3128,14 +3128,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
       }
       setOutput(result);
       }
-    `}},kH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:c}=r,h=new vH(a.shape,o,l,u,c);return n.runWebGLProgram(h,[a,s,i],a.dtype)},IH={kernelName:nd,backendName:"webgl",kernelFunc:kH};function NH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=we({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=Ci(i,e.dtype,"max",r),l=we({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function B_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let x=0;x<w.length;x++)w[x]=a.shape[c[x]];let _=yA(g,a.shape,a.dtype,c,w);p=n.makeTensorInfo(w,a.dtype);let b=n.texData.get(p.dataId);b.values=_}else p=Np(a,c,n);u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("max",u,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,u),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=tL(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let _=n.texData.get(y.dataId);_.values=w}else y=NH(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var SH={kernelName:Ds,backendName:"webgl",kernelFunc:B_},TH=a_+`
+    `}},Aj=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:c}=r,h=new mj(a.shape,o,l,u,c);return n.runWebGLProgram(h,[a,s,i],a.dtype)},yj={kernelName:rd,backendName:"webgl",kernelFunc:Aj};function gj(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=we({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=Ci(i,e.dtype,"max",r),l=we({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function V_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let x=0;x<w.length;x++)w[x]=a.shape[c[x]];let b=yA(g,a.shape,a.dtype,c,w);p=n.makeTensorInfo(w,a.dtype);let _=n.texData.get(p.dataId);_.values=b}else p=Sp(a,c,n);u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("max",u,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,u),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=qP(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let b=n.texData.get(y.dataId);b.values=w}else y=gj(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var xj={kernelName:Ds,backendName:"webgl",kernelFunc:V_},wj=s_+`
   return max(a, b);
-`,EH=`
+`,bj=`
   vec4 result = vec4(max(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+kp+`
+  `+Ip+`
   return result;
-`,CH=on({opSnippet:TH,packedOpSnippet:EH,cpuKernelImpl:nL}),RH={kernelName:Os,backendName:"webgl",kernelFunc:CH};function FH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;Ml(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Bn({inputs:{x:a},backend:n});let h=new bc(c,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var MH={kernelName:zs,backendName:"webgl",kernelFunc:FH};function $H(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,u,l),d=new wA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var DH={kernelName:Tu,backendName:"webgl",kernelFunc:$H},OH=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
+`,_j=on({opSnippet:wj,packedOpSnippet:bj,cpuKernelImpl:XP}),vj={kernelName:Os,backendName:"webgl",kernelFunc:_j};function kj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;Ml(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Bn({inputs:{x:a},backend:n});let h=new _c(c,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var Ij={kernelName:zs,backendName:"webgl",kernelFunc:kj};function Nj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,u,l),d=new wA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var Sj={kernelName:Eu,backendName:"webgl",kernelFunc:Nj},Tj=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
@@ -3181,7 +3181,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},zH=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=u-1-e.padInfo.left,p=o*l*u-1;this.userCode=`
+    `}},Ej=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=u-1-e.padInfo.left,p=o*l*u-1;this.userCode=`
       const ivec3 pads = ivec3(${c}, ${h}, ${d});
 
       void main() {
@@ -3245,14 +3245,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function PH(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new wA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new zH(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var LH={kernelName:ad,backendName:"webgl",kernelFunc:PH};function WH(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;Ml([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,u,1,c,h),p=!0,f=new bc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new OH(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var BH={kernelName:rd,backendName:"webgl",kernelFunc:WH};function VH(e,t,n,r){let a=new bc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new bc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var UH={kernelName:sd,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=R.computePool2DInfo(r.shape,a,s,u,i),[h,d]=VH(r,o,c,l);return[h,d]}};function HH(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=we({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=Ci(i,"float32","mean",r),l=we({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var jH={kernelName:Ps,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,_=new Array(o);for(let N=0;N<_.length;N++)_[N]=r.shape[c[N]];let b=yA(w,r.shape,r.dtype,c,_);f=i.makeTensorInfo(_,r.dtype);let x=i.texData.get(f.dataId);x.values=b}else f=Np(r,c,i);p.push(f),u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("sum",u,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,u),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=HH(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function GH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=we({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=Ci(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=we({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=we({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var qH={kernelName:Ls,backendName:"webgl",kernelFunc:GH},XH=a_+`
+    `}};function Cj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new wA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new Ej(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var Rj={kernelName:sd,backendName:"webgl",kernelFunc:Cj};function Fj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;Ml([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,u,1,c,h),p=!0,f=new _c(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new Tj(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var Mj={kernelName:ad,backendName:"webgl",kernelFunc:Fj};function $j(e,t,n,r){let a=new _c(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new _c(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var Dj={kernelName:id,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=R.computePool2DInfo(r.shape,a,s,u,i),[h,d]=$j(r,o,c,l);return[h,d]}};function Oj(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=we({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=Ci(i,"float32","mean",r),l=we({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var zj={kernelName:Ps,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,b=new Array(o);for(let N=0;N<b.length;N++)b[N]=r.shape[c[N]];let _=yA(w,r.shape,r.dtype,c,b);f=i.makeTensorInfo(b,r.dtype);let x=i.texData.get(f.dataId);x.values=_}else f=Sp(r,c,i);p.push(f),u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("sum",u,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,u),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=Oj(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function Pj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=we({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=Ci(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=we({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=we({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var Lj={kernelName:Ls,backendName:"webgl",kernelFunc:Pj},Wj=s_+`
   return min(a, b);
-`,KH=`
+`,Bj=`
   vec4 result = vec4(min(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+kp+`
+  `+Ip+`
   return result;
-`,ZH=on({opSnippet:XH,packedOpSnippet:KH,cpuKernelImpl:rL}),YH={kernelName:Ws,backendName:"webgl",kernelFunc:ZH},JH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let r=e.length,a=pt(r),s=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
+`,Vj=on({opSnippet:Wj,packedOpSnippet:Bj,cpuKernelImpl:KP}),Uj={kernelName:Ws,backendName:"webgl",kernelFunc:Vj},jj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let r=e.length,a=dt(r),s=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
 
@@ -3281,7 +3281,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         ${a} coords = outC - start;
         setOutput(getX(${o}));
       }
-    `}},QH=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=pt(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=xn("rc",r),l=xn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
+    `}},Hj=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=dt(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=xn("rc",r),l=xn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
         ${a} source = rc;
         if (source < start) {
           source = start * 2 - source - ${h};
@@ -3337,13 +3337,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         ${d}
         setOutput(result);
       }
-    `}},ej=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new QH(r.shape,a,s):new JH(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},tj={kernelName:Eu,backendName:"webgl",kernelFunc:ej},nj=`if (b == 0.0) return NAN;
-  return mod(a, b);`,rj=`
+    `}},Gj=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Hj(r.shape,a,s):new jj(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},qj={kernelName:Cu,backendName:"webgl",kernelFunc:Gj},Xj=`if (b == 0.0) return NAN;
+  return mod(a, b);`,Kj=`
   vec4 result = mod(a, b);
   vec4 isNaN = vec4(equal(b, vec4(0.0)));
-  `+kp+`
+  `+Ip+`
   return result;
-`,aj=on({opSnippet:nj,packedOpSnippet:rj}),sj={kernelName:Do,backendName:"webgl",kernelFunc:aj},ij=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
+`,Zj=on({opSnippet:Xj,packedOpSnippet:Kj}),Yj={kernelName:Do,backendName:"webgl",kernelFunc:Zj},Jj=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
       uniform float seed;
 
       void main() {
@@ -3365,11 +3365,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,XW=Qe({opSnippet:qW}),KW={kernelNam
         // 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)}}},oj=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},Qj=`
 if (a == b) {
   return 1.0;
 };
-return a / b;`,lj=`
+return a / b;`,eH=`
   // vec4 one = vec4(equal(a, b));
   // return one + (vec4(1.0) - one) * a / b;
   vec4 result = a / b;
@@ -3387,14 +3387,14 @@ return a / b;`,lj=`
   }
 
   return result;
-`,V_=on({opSnippet:oj,packedOpSnippet:lj,checkOutOfBounds:!0}),uj={kernelName:Ns,backendName:"webgl",kernelFunc:V_},U_="return a - b;",H_=on({opSnippet:U_,packedOpSnippet:U_,supportsComplex:!0,cpuKernelImpl:hL}),cj={kernelName:ai,backendName:"webgl",kernelFunc:H_};function j_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=B_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),u=we({inputs:{x:o},backend:n,attrs:{shape:l}}),c=H_({inputs:{a,b:u},backend:n}),h=O_({inputs:{x:c},backend:n}),d=xA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=we({inputs:{x:d},backend:n,attrs:{shape:l}}),f=V_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var hj={kernelName:ni,backendName:"webgl",kernelFunc:j_};function dj(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:j_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),u=l.shape[0],c=l.shape[1],h=new ij(u,c,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var pj={kernelName:id,backendName:"webgl",kernelFunc:dj},G_="return -x;";function fj(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=sL(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Ll(r.shape,G_):a=new Xa(r.shape,G_),n.runWebGLProgram(a,[r],r.dtype)}var mj={kernelName:Oo,backendName:"webgl",kernelFunc:fj},Aj=Gr.nonMaxSuppressionV3Impl;function yj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,u=n.readSync(a.dataId),c=n.readSync(s.dataId),{selectedIndices:h}=Aj(u,c,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var gj={kernelName:Po,backendName:"webgl",kernelFunc:yj},xj=Gr.nonMaxSuppressionV4Impl;function wj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=xj(c,h,i,o,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var bj={kernelName:Lo,backendName:"webgl",kernelFunc:wj},_j=Gr.nonMaxSuppressionV5Impl;function vj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=u,{selectedIndices:A,selectedScores:y}=_j(c,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var kj={kernelName:Wo,backendName:"webgl",kernelFunc:vj},Ij=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
+`,U_=on({opSnippet:Qj,packedOpSnippet:eH,checkOutOfBounds:!0}),tH={kernelName:Ns,backendName:"webgl",kernelFunc:U_},j_="return a - b;",H_=on({opSnippet:j_,packedOpSnippet:j_,supportsComplex:!0,cpuKernelImpl:rL}),nH={kernelName:ai,backendName:"webgl",kernelFunc:H_};function G_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=V_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),u=we({inputs:{x:o},backend:n,attrs:{shape:l}}),c=H_({inputs:{a,b:u},backend:n}),h=z_({inputs:{x:c},backend:n}),d=xA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=we({inputs:{x:d},backend:n,attrs:{shape:l}}),f=U_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var rH={kernelName:ni,backendName:"webgl",kernelFunc:G_};function aH(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:G_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),u=l.shape[0],c=l.shape[1],h=new Jj(u,c,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var sH={kernelName:od,backendName:"webgl",kernelFunc:aH},q_="return -x;";function iH(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=YP(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Ll(r.shape,q_):a=new Xa(r.shape,q_),n.runWebGLProgram(a,[r],r.dtype)}var oH={kernelName:Oo,backendName:"webgl",kernelFunc:iH},lH=Gr.nonMaxSuppressionV3Impl;function uH(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,u=n.readSync(a.dataId),c=n.readSync(s.dataId),{selectedIndices:h}=lH(u,c,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var cH={kernelName:Po,backendName:"webgl",kernelFunc:uH},hH=Gr.nonMaxSuppressionV4Impl;function dH(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=hH(c,h,i,o,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var pH={kernelName:Lo,backendName:"webgl",kernelFunc:dH},fH=Gr.nonMaxSuppressionV5Impl;function mH(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=u,{selectedIndices:A,selectedScores:y}=fH(c,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var AH={kernelName:Wo,backendName:"webgl",kernelFunc:mH},yH=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)));
       }
-    `}},Nj=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),u=new Ij(l,s,i,o),c=we({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(u,[c],a.dtype);n.disposeIntermediateTensorInfo(c);let d=[...a.shape,s],p=we({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},Sj={kernelName:Vs,backendName:"webgl",kernelFunc:Nj};function Rp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=vc({inputs:{input:r},backend:n}),s=Rp({inputs:{x:a},backend:n}),i=Cp({inputs:{input:r},backend:n}),o=Rp({inputs:{x:i},backend:n}),l=Ka({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return kA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var Tj={kernelName:al,backendName:"webgl",kernelFunc:Rp};function q_(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=vc({inputs:{input:r},backend:n}),s=q_({inputs:{x:a},backend:n}),i=Cp({inputs:{input:r},backend:n}),o=Rp({inputs:{x:i},backend:n}),l=Ka({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return kA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var Ej={kernelName:Bo,backendName:"webgl",kernelFunc:q_};function Cj(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return vA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(c=>{let h=vA({inputs:{input:c},backend:n,attrs:{dim:a}});return o.push(h),h}),u=N_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var Rj={kernelName:Vo,backendName:"webgl",kernelFunc:Cj},Fj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let r=e.length,a=pt(r),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
+    `}},gH=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),u=new yH(l,s,i,o),c=we({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(u,[c],a.dtype);n.disposeIntermediateTensorInfo(c);let d=[...a.shape,s],p=we({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},xH={kernelName:Vs,backendName:"webgl",kernelFunc:gH};function Fp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=kc({inputs:{input:r},backend:n}),s=Fp({inputs:{x:a},backend:n}),i=Rp({inputs:{input:r},backend:n}),o=Fp({inputs:{x:i},backend:n}),l=Ka({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return kA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var wH={kernelName:al,backendName:"webgl",kernelFunc:Fp};function X_(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=kc({inputs:{input:r},backend:n}),s=X_({inputs:{x:a},backend:n}),i=Rp({inputs:{input:r},backend:n}),o=Fp({inputs:{x:i},backend:n}),l=Ka({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return kA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var bH={kernelName:Bo,backendName:"webgl",kernelFunc:X_};function _H(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return vA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(c=>{let h=vA({inputs:{input:c},backend:n,attrs:{dim:a}});return o.push(h),h}),u=S_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var vH={kernelName:Vo,backendName:"webgl",kernelFunc:_H},kH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let r=e.length,a=dt(r),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
         uniform float value;
@@ -3421,7 +3421,7 @@ return a / b;`,lj=`
           setOutput(getX(${o}));
         }
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},Mj=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=pt(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=xn("rc",r),l=xn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},IH=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=dt(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=xn("rc",r),l=xn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
        if(${u}) {
       `,r===1?"":`}
        rc = outputLoc;
@@ -3446,7 +3446,7 @@ return a / b;`,lj=`
         ${p}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},X_=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Mj(a.shape,s,i):new Fj(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},$j={kernelName:Us,backendName:"webgl",kernelFunc:X_},Dj=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},K_=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new IH(a.shape,s,i):new kH(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},NH={kernelName:Us,backendName:"webgl",kernelFunc:K_},SH=`
   if(a < 0.0 && floor(b) < b){
     return NAN;
   }
@@ -3455,7 +3455,7 @@ return a / b;`,lj=`
   }
   return (round(mod(b, 2.0)) != 1) ?
       pow(abs(a), b) : sign(a) * pow(abs(a), b);
-`,Oj=`
+`,TH=`
   // 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);
@@ -3469,11 +3469,11 @@ return a / b;`,lj=`
   result.a = isExpZero.a ? 1.0 : result.a;
 
   vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
-  `+kp+`
+  `+Ip+`
   return result;
-`,zj=on({opSnippet:Dj,packedOpSnippet:Oj}),Pj={kernelName:Hs,backendName:"webgl",kernelFunc:zj};function Lj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],u=v.parseAxisParam(s,a.shape),c=u,h=R.getAxesPermutation(c,o),d=a;h!=null&&(d=Cn({inputs:{x:a},backend:n,attrs:{perm:h}}),c=R.getInnerMostAxes(c.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",c,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=iL(d.shape,d.dtype,f,c);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,c),A=v.sizeFromShape(m),y=we({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=gd(a.dtype),w=Ci(y,g,"prod",n);p=we({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,u);p=we({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var Wj={kernelName:Uo,backendName:"webgl",kernelFunc:Lj},K_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=oL(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},Bj={kernelName:Cu,backendName:"webgl",kernelFunc:K_},Vj="return 1.0 / x;",Uj=Qe({opSnippet:Vj}),Hj={kernelName:Ho,backendName:"webgl",kernelFunc:Uj},jj=Nr+`
+`,EH=on({opSnippet:SH,packedOpSnippet:TH}),CH={kernelName:js,backendName:"webgl",kernelFunc:EH};function RH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],u=v.parseAxisParam(s,a.shape),c=u,h=R.getAxesPermutation(c,o),d=a;h!=null&&(d=Cn({inputs:{x:a},backend:n,attrs:{perm:h}}),c=R.getInnerMostAxes(c.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",c,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=JP(d.shape,d.dtype,f,c);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,c),A=v.sizeFromShape(m),y=we({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=xd(a.dtype),w=Ci(y,g,"prod",n);p=we({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,u);p=we({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var FH={kernelName:Uo,backendName:"webgl",kernelFunc:RH},Z_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=QP(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},MH={kernelName:Ru,backendName:"webgl",kernelFunc:Z_},$H="return 1.0 / x;",DH=Qe({opSnippet:$H}),OH={kernelName:jo,backendName:"webgl",kernelFunc:DH},zH=Nr+`
   return (x < 0.0) ? 0.0 : x;
-`,Gj=`
+`,PH=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3483,9 +3483,9 @@ return a / b;`,lj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,qj=Qe({opSnippet:jj,packedOpSnippet:Gj}),Xj={kernelName:Gs,backendName:"webgl",kernelFunc:qj},Kj=Nr+`
+`,LH=Qe({opSnippet:zH,packedOpSnippet:PH}),WH={kernelName:Gs,backendName:"webgl",kernelFunc:LH},BH=Nr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,Zj=`
+`,VH=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3495,7 +3495,7 @@ return a / b;`,lj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,Yj=Qe({opSnippet:Kj,packedOpSnippet:Zj}),Jj={kernelName:Xs,backendName:"webgl",kernelFunc:Yj},Qj=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+`,UH=Qe({opSnippet:BH,packedOpSnippet:VH}),jH={kernelName:Xs,backendName:"webgl",kernelFunc:UH},HH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${u[0]/c[0]},
           ${u[1]/c[1]});
@@ -3528,7 +3528,7 @@ return a / b;`,lj=`
 
         setOutput(newValue);
       }
-    `}},eG=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}},GH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec3 effectiveInputOverOutputRatioRC = vec3(
           ${u[0]/c[0]},
           ${u[1]/c[1]},
@@ -3605,7 +3605,7 @@ return a / b;`,lj=`
 
         setOutput(newValue);
       }
-    `}};function tG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new eG(a.shape,l,u,s,i):new Qj(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],"float32")}var nG={kernelName:qs,backendName:"webgl",kernelFunc:tG},rG=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function qH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new GH(a.shape,l,u,s,i):new HH(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],"float32")}var XH={kernelName:qs,backendName:"webgl",kernelFunc:qH},KH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3686,7 +3686,7 @@ return a / b;`,lj=`
 
         setOutput(accumulator);
       }
-    `}};function aG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new rG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var sG={kernelName:ud,backendName:"webgl",kernelFunc:aG},iG=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};function ZH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new KH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var YH={kernelName:cd,backendName:"webgl",kernelFunc:ZH},JH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${u[0]/c[0]},
           ${u[1]/c[1]});
@@ -3708,7 +3708,7 @@ return a / b;`,lj=`
 
         setOutput(newValue);
       }
-    `}};function oG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=new iG(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],a.dtype)}var lG={kernelName:Ru,backendName:"webgl",kernelFunc:oG},uG=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function QH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=new JH(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],a.dtype)}var eG={kernelName:Fu,backendName:"webgl",kernelFunc:QH},tG=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3778,17 +3778,17 @@ return a / b;`,lj=`
 
         setOutput(accumulator);
       }
-    `}};function cG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new uG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var hG={kernelName:ld,backendName:"webgl",kernelFunc:cG},dG=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
+    `}};function nG(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new tG(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var rG={kernelName:ud,backendName:"webgl",kernelFunc:nG},aG=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
         void main() {
           int coord = getOutputCoords();
           setOutput(getX(${e[0]} - coord - 1));
         }
-      `;return}let r=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>r(o)).join(","),s=pt(n);this.userCode=`
+      `;return}let r=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>r(o)).join(","),s=dt(n);this.userCode=`
       void main() {
         ${s} coords = getOutputCoords();
         setOutput(getX(${a}));
       }
-    `}},pG=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-${n} tensor is not yet supported`);this.outputShape=e;let r=xn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=pt(n);n===1?this.userCode=`
+    `}},sG=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=xn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=dt(n);n===1?this.userCode=`
         void main(){
           int rc = getOutputCoords();
           vec4 result = vec4(0.);
@@ -3816,7 +3816,7 @@ return a / b;`,lj=`
           }
           setOutput(result);
         }
-    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function u(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function c(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function fG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return Bn({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new pG(a.shape,o):new dG(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var mG={kernelName:Ks,backendName:"webgl",kernelFunc:fG},AG=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
+    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function u(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function c(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function iG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return Bn({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new sG(a.shape,o):new aG(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var oG={kernelName:Ks,backendName:"webgl",kernelFunc:iG},lG=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
         vec3 fill = vec3(${t.join(",")});
         float outputValue = fill[coords[3]];`,this.userCode=`
         uniform vec4 params;
@@ -3836,7 +3836,7 @@ return a / b;`,lj=`
           }
           setOutput(outputValue);
         }
-    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},yG={kernelName:sl,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new AG(r.shape,s),[u,c]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(u,c,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},gG=`
+    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},uG={kernelName:sl,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new lG(r.shape,s),[u,c]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(u,c,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},cG=`
   // OpenGL ES does not support round function.
   // The algorithm is based on banker's rounding.
   float base = floor(x);
@@ -3851,7 +3851,7 @@ return a / b;`,lj=`
       return base + 1.0;
     }
   }
-`,xG=Qe({opSnippet:gG}),wG={kernelName:Zs,backendName:"webgl",kernelFunc:xG},bG="return inversesqrt(x);",_G=Qe({opSnippet:bG,cpuKernelImpl:lL}),vG={kernelName:Ys,backendName:"webgl",kernelFunc:_G},Z_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=pt(a.length),l=pt(s.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
+`,hG=Qe({opSnippet:cG}),dG={kernelName:Zs,backendName:"webgl",kernelFunc:hG},pG="return inversesqrt(x);",fG=Qe({opSnippet:pG,cpuKernelImpl:eL}),mG={kernelName:Ys,backendName:"webgl",kernelFunc:fG},Y_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=dt(a.length),l=dt(s.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
         ${o} strides = ${o}(${a});
 
         void main() {
@@ -3871,7 +3871,7 @@ return a / b;`,lj=`
           }
           setOutput(mix(getDefaultValue(), sum, float(found)));
         }
-      `}};function kG(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:u,strides:c,outputSize:h}=R.calculateShapes(s,a,i),d=[h/u,u];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=we({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=we({inputs:{x:s},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new Z_(l,o,p.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=we({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var IG={kernelName:Go,backendName:"webgl",kernelFunc:kG},NG=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);r=o.join(),a=l.join()}let s=pt(n);this.userCode=`
+      `}};function AG(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:u,strides:c,outputSize:h}=R.calculateShapes(s,a,i),d=[h/u,u];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=we({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=we({inputs:{x:s},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new Y_(l,o,p.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=we({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var yG={kernelName:Go,backendName:"webgl",kernelFunc:AG},gG=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);r=o.join(),a=l.join()}let s=dt(n);this.userCode=`
       void main() {
         ${s} resRC = getOutputCoords();
         float cVal = getC(${r});
@@ -3881,21 +3881,21 @@ return a / b;`,lj=`
           setOutput(getB(${a}));
         }
       }
-    `}};function SG(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new NG(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],cr(a.dtype,s.dtype))}var TG={kernelName:qo,backendName:"webgl",kernelFunc:SG},EG=`
+    `}};function xG(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new gG(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],cr(a.dtype,s.dtype))}var wG={kernelName:qo,backendName:"webgl",kernelFunc:xG},bG=`
   // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
   // see: https://arxiv.org/abs/1706.02515
   float scaleAlpha = ${R.SELU_SCALEALPHA};
   float scale = ${R.SELU_SCALE};
   return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
-`,CG=Qe({opSnippet:EG}),RG={kernelName:Xo,backendName:"webgl",kernelFunc:CG},FG="return 1.0 / (1.0 + exp(-1.0 * x));",MG=Qe({opSnippet:FG}),$G={kernelName:Qs,backendName:"webgl",kernelFunc:MG},DG=`
+`,_G=Qe({opSnippet:bG}),vG={kernelName:Xo,backendName:"webgl",kernelFunc:_G},kG="return 1.0 / (1.0 + exp(-1.0 * x));",IG=Qe({opSnippet:kG}),NG={kernelName:Qs,backendName:"webgl",kernelFunc:IG},SG=`
   if (isnan(x)) { return 0.0; }
   return sign(x);
-`,OG=Qe({opSnippet:DG}),zG={kernelName:Yo,backendName:"webgl",kernelFunc:OG},PG=u_+`
+`,TG=Qe({opSnippet:SG}),EG={kernelName:Yo,backendName:"webgl",kernelFunc:TG},CG=c_+`
   return sin(x);
-`,LG=Qe({opSnippet:PG}),WG={kernelName:Js,backendName:"webgl",kernelFunc:LG},BG=`
+`,RG=Qe({opSnippet:CG}),FG={kernelName:Js,backendName:"webgl",kernelFunc:RG},MG=`
   float e2x = exp(x);
   return (e2x - 1.0 / e2x) / 2.0;
-`,VG=Qe({opSnippet:BG}),UG={kernelName:Zo,backendName:"webgl",kernelFunc:VG},HG=`
+`,$G=Qe({opSnippet:MG}),DG={kernelName:Zo,backendName:"webgl",kernelFunc:$G},OG=`
   float epsilon = 1.1920928955078125e-7;
   float threshold = log(epsilon) + 2.0;
 
@@ -3915,9 +3915,9 @@ return a / b;`,lj=`
     result = log(exp_x + 1.0);
   }
   return result;
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     return x > 0.0 ? 1.0 : float(${t.alpha});
-  `,s=new Xa(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var lq={kernelName:Da,backendName:"webgl",kernelFunc:oq},uq=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=pt(n.length),s=pt(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,u)=>(o++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
+  `,s=new Xa(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var eq={kernelName:Da,backendName:"webgl",kernelFunc:QG},tq=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=dt(n.length),s=dt(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,u)=>(o++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
       ${a} begin = ${a}(${e});
       ${a} strides = ${a}(${t});
 
@@ -3925,15 +3925,15 @@ return a / b;`,lj=`
         ${s} coords = getOutputCoords();
         setOutput(getX(${i}));
       }
-    `}};function cq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=fn.sliceInfo(a.shape,s,i,o,l,u,c,h,d),w=we({inputs:{x:a},backend:n,attrs:{shape:y}}),_;if(p){let x=_c({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});_=we({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))_=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let x=n.texData.get(w.dataId).values,N=Ue(w.shape,w.dtype,x),S=cL(g,N,m,f);_=n.makeTensorInfo(g,w.dtype,S.values)}else{let x=new uq(f,m,g);_=n.runWebGLProgram(x,[w],w.dtype)}let b=we({inputs:{x:_},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(_),b}var hq={kernelName:el,backendName:"webgl",kernelFunc:cq},dq="return tan(x);",pq=Qe({opSnippet:dq}),fq={kernelName:tl,backendName:"webgl",kernelFunc:pq},mq=`
+    `}};function nq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=fn.sliceInfo(a.shape,s,i,o,l,u,c,h,d),w=we({inputs:{x:a},backend:n,attrs:{shape:y}}),b;if(p){let x=vc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});b=we({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))b=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let x=n.texData.get(w.dataId).values,N=Ue(w.shape,w.dtype,x),T=nL(g,N,m,f);b=n.makeTensorInfo(g,w.dtype,T.values)}else{let x=new tq(f,m,g);b=n.runWebGLProgram(x,[w],w.dtype)}let _=we({inputs:{x:b},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(b),_}var rq={kernelName:el,backendName:"webgl",kernelFunc:nq},aq="return tan(x);",sq=Qe({opSnippet:aq}),iq={kernelName:tl,backendName:"webgl",kernelFunc:sq},oq=`
   float e2x = exp(-2.0 * abs(x));
   return sign(x) * (1.0 - e2x) / (1.0 + e2x);
-`,Aq=Qe({opSnippet:mq}),yq={kernelName:si,backendName:"webgl",kernelFunc:Aq},xq=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=pt(this.rank),a=gq(e);this.userCode=`
+`,lq=Qe({opSnippet:oq}),uq={kernelName:si,backendName:"webgl",kernelFunc:lq},hq=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=dt(this.rank),a=cq(e);this.userCode=`
       void main() {
         ${r} resRC = getOutputCoords();
         setOutput(getA(${a}));
       }
-    `}};function gq(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function J_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(c=>v.decodeString(c)),l=Ue(a.shape,a.dtype,o),u=dL(l,s);return n.makeTensorInfo(u.shape,u.dtype,u.values)}let i=new xq(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var wq={kernelName:$a,backendName:"webgl",kernelFunc:J_};function bq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,u]=pL(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var _q={kernelName:nl,backendName:"webgl",kernelFunc:bq},vq=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
+    `}};function cq(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function Q_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(c=>v.decodeString(c)),l=Ue(a.shape,a.dtype,o),u=aL(l,s);return n.makeTensorInfo(u.shape,u.dtype,u.values)}let i=new hq(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var dq={kernelName:$a,backendName:"webgl",kernelFunc:Q_};function pq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,u]=sL(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var fq={kernelName:nl,backendName:"webgl",kernelFunc:pq},mq=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
             float mapCoord(float outCoord, float len) {
               float inCoord = outCoord;
               if(${o} == 2) {
@@ -4045,7 +4045,7 @@ return a / b;`,lj=`
               }
               setOutput(outputValue);
             }
-        `}};function kq(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=r,[c,h,d,p]=a.shape,[f,m]=u!=null?u:[h,d],A=[c,f,m,p],y=new vq(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var Iq={kernelName:hd,backendName:"webgl",kernelFunc:kq};function Nq(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;Ml(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=fL(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([u.length],"int32",u)]}var Sq={kernelName:dd,backendName:"webgl",kernelFunc:Nq};function Tq(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],u=new Array(o-1),c=0;for(let m=0;m<o;m++)m!==s&&(u[c++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=_c({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=we({inputs:{x:A},backend:n,attrs:{shape:u}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var Eq={kernelName:rl,backendName:"webgl",kernelFunc:Tq},Cq=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,h=`
+        `}};function Aq(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=r,[c,h,d,p]=a.shape,[f,m]=u!=null?u:[h,d],A=[c,f,m,p],y=new mq(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var yq={kernelName:dd,backendName:"webgl",kernelFunc:Aq};function gq(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;Ml(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=iL(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([u.length],"int32",u)]}var xq={kernelName:pd,backendName:"webgl",kernelFunc:gq};function wq(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],u=new Array(o-1),c=0;for(let m=0;m<o;m++)m!==s&&(u[c++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=vc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=we({inputs:{x:A},backend:n,attrs:{shape:u}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var bq={kernelName:rl,backendName:"webgl",kernelFunc:wq},_q=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,h=`
         sumValue += dot(values, segFilter);
     `,d="";a%n>0&&(d=`
         if (inIdx < 0 || inIdx >= ${a}) {
@@ -4151,26 +4151,26 @@ return a / b;`,lj=`
         }
         setOutput(${l});
       }
-    `}};function Rq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r,o=a.shape.length,l=[],u=0,c=R.getAxesPermutation([u],o),h=a;c!=null&&(h=Cn({inputs:{x:a},backend:n,attrs:{perm:c}}),l.push(h),u=R.getInnerMostAxes(1,o)[0]);let d=R.segment_util.computeOutShape(h.shape,u,i),p=v.sizeFromShape([h.shape[u]]),f=we({inputs:{x:h},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=gd(a.dtype),A=(_,b,x,N,S)=>{let T=_.shape[0],M=_.shape[1],D=R.segment_util.segOpComputeOptimalWindowSize(M,S),z={windowSize:D,inSize:M,batchSize:T,numSegments:S},B=new Cq(z,b),U=n.compileAndRun(B,[_,x],N);if(l.push(U),U.shape[1]===S)return U;let H=K_({backend:n,attrs:{start:0,stop:S,step:1,dtype:"float32"}}),X=J_({inputs:{x:H},backend:n,attrs:{reps:[M/D]}});return l.push(H),l.push(X),A(U,b,X,N,S)},y=A(f,"unsortedSegmentSum",s,m,i),g=we({inputs:{x:y},backend:n,attrs:{shape:d}}),w=g;if(c!=null){l.push(g);let _=R.getUndoAxesPermutation(c);w=Cn({inputs:{x:w},backend:n,attrs:{perm:_}})}return 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DK={kernelName:Wo,backendName:"wasm",setupFunc:MK,kernelFunc:$K},OK=!1,zK=wn(zo,OK,"bool"),T3;function PK(e){T3=e.wasm.cwrap(Vs,null,["number","number","number","number","number"])}function LK(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=n.makeOutput([...a.shape,s],"int32"),u=n.dataIdMap.get(l.dataId).id,c=n.dataIdMap.get(a.dataId).id;return T3(c,s,i,o,u),l}var WK={kernelName:Vs,backendName:"wasm",setupFunc:PK,kernelFunc:LK};function BK(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(r).fill(1),r}var VK={kernelName:Bo,backendName:"wasm",kernelFunc:BK};function UK(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return NA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let 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Found: ${this.outputs.map(y=>y.name)}`),this.inputLayers=[],this.inputLayersNodeIndices=[],this.inputLayersTensorIndices=[],this.outputLayers=[],this.outputLayersNodeIndices=[],this.outputLayersTensorIndices=[],this.layers=[],this.internalContainerRefs=[];for(let y of this.outputs){let g=y.sourceLayer,w=y.nodeIndex,_=y.tensorIndex;this.outputLayers.push(g),this.outputLayersNodeIndices.push(w),this.outputLayersTensorIndices.push(_)}for(let y of this.inputs){let g=y.sourceLayer,w=y.nodeIndex,_=y.tensorIndex;Kr(w===0,"input layer has >1 nodes"),Kr(_===0,"input layer has >1 tensors"),this.inputLayers.push(g),this.inputLayersNodeIndices.push(w),this.inputLayersTensorIndices.push(_)}this.inputNames=[],this.outputNames=[],this.feedInputShapes=[],this.feedInputNames=[],this.feedOutputNames=[];for(let y=0;y<this.inputLayers.length;y++){let g=this.inputLayers[y];if(!(g instanceof ql))throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${e.inputs}. 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Provided ${n} not understood: ${JSON.stringify(e)}`)}function X7(e,t){return une(e,t,"classWeight")}async function K7(e,t,n,r){if(t!=null||r!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let a=W(()=>{if(e.shape.length===1)return e.clone();if(e.shape.length===2)if(e.shape[1]>1){let o=1;return e.argMax(o)}else{if(e.shape[1]===1)return e.reshape([e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await a.data());Re(a);let i=[];return s.forEach(o=>{if(n[o]==null)throw new Error(`classWeight must contain all classes in the training data. 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Use LayersModel.compile(modelCompileConfig)."),v.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),v.assert(n.epochs!=null&&n.epochs>0&&Number.isInteger(n.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`),v.assert(!r||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),v.assert(n.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};_y.className="ThresholdedReLU";ae.registerClass(_y);var vy=class extends Je{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new my().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Be(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}};vy.className="Softmax";ae.registerClass(vy);function Yl(e,t,n){if(typeof e=="number")return Ri(e,t);if(e.length!==t)throw new V(`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 ${a}`)}return e}function Mr(e,t,n,r,a=1){if(e==null)return e;let s=t+(t-1)*(a-1),i;return n==="same"?i=e:i=e-s+1,Math.floor((i+r-1)/r)}function i0(e,t,n,r){if(e==null)return null;if(r==="valid")e=e*t+Ja([n-t,0]);else if(r==="same")e=e*t;else throw new V(`Unsupport padding mode: ${r}.`);return e}function ky(e,t){return W(()=>(Mt(t),t==="channelsFirst"?ot(e,[0,2,3,1]):e))}function xv(e,t){return W(()=>(Mt(t),t==="channelsFirst"?ot(e,[0,2,3,4,1]):e))}function $ne(e,t,n,r=1,a="valid",s,i=1){return W(()=>{if(s==null&&(s=Tr()),Mt(s),e.shape.length!==3)throw new V(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new V(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new V(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=ot(e,[0,2,1])),a==="causal")throw new Pe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=Sd(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Yr(o,n)),o})}function wv(e,t,n,r=[1,1],a="valid",s,i,o=null){return W(()=>{if(s==null&&(s=Tr()),Mt(s),e.rank!==3&&e.rank!==4)throw new V(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new V(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=ky(e,s);if(a==="causal")throw new Pe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Ga.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=ot(l,[0,3,1,2])),l})}function Dne(e,t,n,r=[1,1,1],a="valid",s,i){return W(()=>{if(s==null&&(s=Tr()),Mt(s),e.rank!==4&&e.rank!==5)throw new V(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new V(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=xv(e,s);if(a==="causal")throw new Pe("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=pm(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Yr(o,n)),s==="channelsFirst"&&(o=ot(o,[0,4,1,2,3])),o})}var Iy=class extends Je{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Iy.verifyArgs(t),this.rank=e,Jt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Pe(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Yl(t.kernelSize,e,"kernelSize"),this.strides=Yl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,rr(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Mt(this.dataFormat),this.activation=ts(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=_t(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=qt(t.biasConstraint),this.biasRegularizer=vt(t.biasRegularizer),this.activityRegularizer=vt(t.activityRegularizer),this.dilationRate=Yl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new V(`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 V(`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 V(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Kr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!MA(e.kernelSize,"number",1,3))throw new V(`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:es(this.activation),useBias:this.useBias,biasInitializer:Et(this.biasInitializer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),biasConstraint:Gt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Bc=class extends Iy{constructor(e,t){super(e,t);this.kernel=null,Bc.verifyArgs(t),this.filters=t.filters,Jt(this.filters,"filters"),this.kernelInitializer=_t(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=qt(t.kernelConstraint),this.kernelRegularizer=vt(t.kernelRegularizer)}build(e){e=ft(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],r=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",r,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return W(()=>{e=Be(e);let n,r=this.bias==null?null:this.bias.read(),a=s7(this.activation.getClassName());if(a!=null&&this.rank===2)n=wv(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,a);else{if(this.rank===1)n=$ne(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=wv(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=Dne(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Pe("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=ft(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let a=0;a<n.length;++a){let s=Mr(n[a],this.kernelSize[a],this.padding,this.strides[a],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[a]);t.push(s)}let r=[e[0]];return this.dataFormat==="channelsLast"?(r=r.concat(t),r.push(this.filters)):(r.push(this.filters),r=r.concat(t)),r}getConfig(){let e={filters:this.filters,kernelInitializer:Et(this.kernelInitializer),kernelRegularizer:mt(this.kernelRegularizer),kernelConstraint:Gt(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 V(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Vc=class extends Bc{constructor(e){super(2,e);Vc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!MA(e.kernelSize,"number",1,2))throw new V(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Vc.className="Conv2D";ae.registerClass(Vc);var o0=class extends Bc{constructor(e){super(3,e);o0.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 V(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};o0.className="Conv3D";ae.registerClass(o0);var Ny=class extends Vc{constructor(e){super(e);if(this.inputSpec=[new Qt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=ft(e),e.length!==4)throw new V("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Qt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return W(()=>{let n=Be(e);if(n.shape.length!==4)throw new V(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],u=this.kernelSize[0],c=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=i0(o,h,u,this.padding),f=i0(l,d,c,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=ot(n,[0,2,3,1]));let A=Td(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=ot(A,[0,3,1,2])),this.bias!=null&&(A=Yr(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=ft(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=i0(t[r],o,s,this.padding),t[a]=i0(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Ny.className="Conv2DTranspose";ae.registerClass(Ny);var bv=class extends Bc{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 V("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new V("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 V(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=_t(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=vt(t.depthwiseRegularizer),this.depthwiseConstraint=qt(t.depthwiseConstraint),this.pointwiseInitializer=_t(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=vt(t.pointwiseRegularizer),this.pointwiseConstraint=qt(t.pointwiseConstraint)}build(e){if(e=ft(e),e.length<this.rank+2)throw new V(`Inputs to SeparableConv${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 V(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Qt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return W(()=>{e=Be(e);let n;if(this.rank===1)throw new Pe("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=ot(e,[0,2,3,1])),n=Rm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Yr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=ot(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=Et(this.depthwiseInitializer),e.pointwiseInitializer=Et(this.pointwiseInitializer),e.depthwiseRegularizer=mt(this.depthwiseRegularizer),e.pointwiseRegularizer=mt(this.pointwiseRegularizer),e.depthwiseConstraint=Gt(this.depthwiseConstraint),e.pointwiseConstraint=Gt(this.pointwiseConstraint),e}};bv.className="SeparableConv";var Sy=class extends bv{constructor(e){super(2,e)}};Sy.className="SeparableConv2D";ae.registerClass(Sy);var l0=class extends Bc{constructor(e){super(1,e);l0.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"&&!MA(e.kernelSize,"number",1,1))throw new V(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};l0.className="Conv1D";ae.registerClass(l0);var Ty=class extends Je{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 W(()=>{if(e=Be(e),this.dataFormat==="channelsLast"){let n=Pp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Pp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Pp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Pp(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}};Ty.className="Cropping2D";ae.registerClass(Ty);var Ey=class extends Je{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,Mt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,nee(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 W(()=>{let n=Be(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=ot(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return ot(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Ey.className="UpSampling2D";ae.registerClass(Ey);function One(e,t,n=[1,1],r="valid",a,s){return W(()=>{a==null&&(a=Tr()),Mt(a);let i=ky(e,a);if(e.rank!==4)throw new V(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new V(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=xl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=ot(i,[0,3,1,2])),i})}var Cy=class extends Iy{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=_t(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=qt(e.depthwiseConstraint),this.depthwiseRegularizer=vt(e.depthwiseRegularizer)}build(e){if(e=ft(e),e.length<4)throw new V(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${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 W(()=>{e=Be(e);let n=One(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Yr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=ft(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Mr(t,this.kernelSize[0],this.padding,this.strides[0]),s=Mr(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Et(this.depthwiseInitializer),e.depthwiseRegularizer=mt(this.depthwiseRegularizer),e.depthwiseConstraint=Gt(this.depthwiseRegularizer),e}};Cy.className="DepthwiseConv2D";ae.registerClass(Cy);function _v(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new V("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function vv(e,t,n,r=!1,a,s,i=!1,o=!1){return W(()=>{let l=t.shape.length;if(l<3)throw new V(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Cr(2,l));if(t=ot(t,u),s!=null)throw new Pe("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=mn(a,-1)),a=ot(a,u)),r&&(t=Ln(t,0),a!=null&&(a=Ln(a,0)));let c=[],h,d=n,p=t.shape[0],f=pr(t),m;a!=null&&(m=pr(a));for(let y=0;y<p;++y){let g=f[y],w=W(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let _=W(()=>{let b=m[y],x=Pn(b).sub(b),N=w[0].mul(b).add(d[0].mul(x)),S=d.map((T,M)=>w[1][M].mul(b).add(T.mul(x)));return{output:N,newStates:S}});h=_.output,d=_.newStates}o&&c.push(h)}let A;return o&&(A=An(c,1)),[h,A,d]})}var Jr=class extends Je{constructor(e){super(e);let t;if(e.cell==null)throw new V("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new u0({cells:e.cell}):t=e.cell,t.stateSize==null)throw new V("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new Qt({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Cr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){QA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return W(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new Pe("Constants support is not implemented in RNN yet.");QA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Qt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new Pe("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new V(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Qt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){W(()=>{if(!this.stateful)throw new Aa("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new V("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=>Ot([n,r])):this.states_=[Ot([n,this.cell.stateSize])];else if(e==null)Re(this.states_),this.keptStates!=null&&(Re(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Ot([n,r])):this.states_[0]=Ot([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):Re(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new V(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Zt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=_v(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Qt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof Rr){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let c=super.apply(o,t);return this.inputSpec=u,c}else return super.apply(e,t)}call(e,t){return W(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Be(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new V(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=vv((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],c=o[2];this.stateful&&this.resetStates(c,r);let h=this.returnSequences?u:l;return this.returnState?[h].concat(c):h})}getInitialState(e){return W(()=>{let t=Ot(e.shape);return t=Fe(t,[1,2]),t=Fc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?LA(t,[1,n]):t):this.cell.stateSize>1?[LA(t,[1,this.cell.stateSize])]:[t]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){let e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(t.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===Jr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=Fr(r,n);return new e(Object.assign(t,{cell:a}))}};Jr.className="RNN";ae.registerClass(Jr);var Dc=class extends Je{},c0=class extends Dc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Jt(this.units,"units"),this.activation=ts(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=_t(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=_t(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=_t(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=qt(e.kernelConstraint),this.recurrentConstraint=qt(e.recurrentConstraint),this.biasConstraint=qt(e.biasConstraint),this.dropout=Gl([1,Ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Gl([1,Ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ft(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 W(()=>{if(e=e,e.length!==2)throw new V(`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=ns({ones:()=>Pn(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ns({ones:()=>Pn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Zr(P(e,s),this.kernel.read()):a=Zr(e,this.kernel.read()),this.bias!=null&&(a=Yr(a,this.bias.read())),i!=null&&(n=P(n,i));let o=ie(a,Zr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:es(this.activation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),recurrentInitializer:Et(this.recurrentInitializer),biasInitializer:Et(this.biasInitializer),kernelRegularizer:mt(this.kernelRegularizer),recurrentRegularizer:mt(this.recurrentRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Gt(this.kernelConstraint),recurrentConstraint:Gt(this.recurrentConstraint),biasConstraint:Gt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};c0.className="SimpleRNNCell";ae.registerClass(c0);var Ry=class extends Jr{constructor(e){e.cell=new c0(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};Ry.className="SimpleRNN";ae.registerClass(Ry);var h0=class extends Dc{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 V("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Jt(this.units,"units"),this.activation=ts(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ts(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=_t(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=_t(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=_t(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=qt(e.kernelConstraint),this.recurrentConstraint=qt(e.recurrentConstraint),this.biasConstraint=qt(e.biasConstraint),this.dropout=Gl([1,Ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Gl([1,Ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ft(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 W(()=>{if(e=e,e.length!==2)throw new V(`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=ns({ones:()=>Pn(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ns({ones:()=>Pn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let u=Zr(e,this.kernel.read());this.useBias&&(u=Yr(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,s[0]));let c=this.recurrentKernel.read(),[h,d]=Ht(c,[2*this.units,this.units],c.rank-1),p=Zr(r,h),[f,m,A]=Ht(u,3,u.rank-1),[y,g]=Ht(p,2,p.rank-1);i=this.recurrentActivation.apply(ie(f,y)),o=this.recurrentActivation.apply(ie(m,g));let w=Zr(P(o,r),d);l=this.activation.apply(ie(A,w));let _=ie(P(i,r),P(ie(1,St(i)),l));return[_,_]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:es(this.activation),recurrentActivation:es(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),recurrentInitializer:Et(this.recurrentInitializer),biasInitializer:Et(this.biasInitializer),kernelRegularizer:mt(this.kernelRegularizer),recurrentRegularizer:mt(this.recurrentRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Gt(this.kernelConstraint),recurrentConstraint:Gt(this.recurrentConstraint),biasConstraint:Gt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};h0.className="GRUCell";ae.registerClass(h0);var Fy=class extends Jr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new h0(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Fy.className="GRU";ae.registerClass(Fy);var Uc=class extends Dc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Jt(this.units,"units"),this.activation=ts(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ts(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=_t(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=_t(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=_t(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=qt(e.kernelConstraint),this.recurrentConstraint=qt(e.recurrentConstraint),this.biasConstraint=qt(e.biasConstraint),this.dropout=Gl([1,Ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Gl([1,Ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=ft(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends Ar{apply(i,o){let l=a.apply([s]),u=new Wp().apply([s]),c=a.apply([s*2]);return m7(m7(l,u),c)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return W(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new V(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ns({ones:()=>Pn(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ns({ones:()=>Pn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,c;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let h=Zr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,i[0])),h=ie(h,Zr(r,this.recurrentKernel.read())),this.useBias&&(h=Yr(h,this.bias.read()));let[d,p,f,m]=Ht(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),u=ie(P(l,a),P(o,this.activation.apply(f))),c=this.recurrentActivation.apply(m);let A=P(c,this.activation.apply(u));return[A,A,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:es(this.activation),recurrentActivation:es(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),recurrentInitializer:Et(this.recurrentInitializer),biasInitializer:Et(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:mt(this.kernelRegularizer),recurrentRegularizer:mt(this.recurrentRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Gt(this.kernelConstraint),recurrentConstraint:Gt(this.recurrentConstraint),biasConstraint:Gt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Uc.className="LSTMCell";ae.registerClass(Uc);var My=class extends Jr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Uc(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};My.className="LSTM";ae.registerClass(My);var u0=class extends Dc{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return W(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){QA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{$i(`RNNCell_${r}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(Fr(a,n));return new e({cells:r})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return ey(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}ty(t)}};u0.className="StackedRNNCells";ae.registerClass(u0);function ns(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>y7(t(),n),i=()=>$c(s,t,r);return!a||a<=1?Zt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Zt(o.clone()))}var zne=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},kv=class extends Jr{constructor(e){if(e.unroll)throw new Pe("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Pe("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Qt({ndim:5})]}call(e,t){return W(()=>{if(this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new V("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return W(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Ot(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){W(()=>{if(!this.stateful)throw new Aa("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ot(a)):this.states_=[Ot(a)];else if(e==null)Re(this.states_),this.keptStates!=null&&(Re(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ot(a)):this.states_[0]=Ot(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):Re(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new V(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Zt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],u=e[o?4:3],c=Mr(l,r[0],a,s[0],i[0]),h=Mr(u,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,c,h]:[c,h,n]]}};kv.className="ConvRNN2D";var d0=class extends Uc{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Jt(this.filters,"filters"),this.kernelSize=Yl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Jt(o,"kernelSize")),this.strides=Yl(r||1,2,"strides"),this.strides.forEach(o=>Jt(o,"strides")),this.padding=a||"valid",rr(this.padding),this.dataFormat=s||"channelsLast",Mt(this.dataFormat),this.dilationRate=Yl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Jt(o,"dilationRate"))}build(e){var t;e=ft(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;o=new(t=class extends Ar{apply(c,h){let d=l.apply([u]),p=Hr([u]),f=l.apply([u*2]);return BA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return W(()=>{if(e.length!==3)throw new V(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ns({ones:()=>Pn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,se,ne)=>!se||!se[ne]?Y:P(se[ne],Y),u=l(r,o,0),c=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ns({ones:()=>Pn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,_,b,x]=Ht(this.kernel.read(),i,g),[N,S,T,M]=this.useBias?Ht(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,w,N,this.padding),c=this.inputConv(c,_,S,this.padding),h=this.inputConv(h,b,T,this.padding),d=this.inputConv(d,x,M,this.padding);let[D,z,B,U]=Ht(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,D),m=this.recurrentConv(m,z),A=this.recurrentConv(A,B),y=this.recurrentConv(y,U);let H=this.recurrentActivation.apply(ie(u,f)),X=this.recurrentActivation.apply(ie(c,m)),j=ie(P(X,s),P(H,this.activation.apply(ie(h,A)))),ee=P(this.recurrentActivation.apply(ie(d,y)),this.activation.apply(j));return[ee,ee,j]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=zne(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=ca(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Yr(a,n,this.dataFormat):a}recurrentConv(e,t){return ca(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};d0.className="ConvLSTM2DCell";ae.registerClass(d0);var $y=class extends kv{constructor(e){let t=new d0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};$y.className="ConvLSTM2D";ae.registerClass($y);var p0=class extends Je{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 W(()=>{this.invokeCallHook(e,t);let n=Be(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return $c(()=>y7(n,this.rate,a,this.seed),()=>n,r)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};p0.className="Dropout";ae.registerClass(p0);var Dy=class extends p0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Dy.className="SpatialDropout1D";ae.registerClass(Dy);var Oy=class extends Je{constructor(e){super(e);if(this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,Jt(this.units,"units"),this.activation=ts(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=_t(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=_t(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=qt(e.kernelConstraint),this.biasConstraint=qt(e.biasConstraint),this.kernelRegularizer=vt(e.kernelRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.activityRegularizer=vt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=ft(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=ft(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Be(e),r=s7(this.activation.getClassName()),a;return r!=null?a=Zr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Zr(n,this.kernel.read()),this.bias!=null&&(a=Yr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:es(this.activation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),biasInitializer:Et(this.biasInitializer),kernelRegularizer:mt(this.kernelRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Gt(this.kernelConstraint),biasConstraint:Gt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Oy.className="Dense";ae.registerClass(Oy);var zy=class extends Je{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=ft(e);for(let t of e.slice(1))if(t==null)throw new V(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). 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W(()=>(e=Be(e),iee(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Ly.className="RepeatVector";ae.registerClass(Ly);var Wy=class extends Je{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new V("Can only specifiy one unknown dimension.");else a*=l}let i=Ya(e);if(s!==null){if(a===0||i%a!=0)throw new V(n);r[s]=i/a}else if(i!==a)throw new V(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 W(()=>{this.invokeCallHook(e,t);let n=Be(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Wy.className="Reshape";ae.registerClass(Wy);var By=class extends Je{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=Cr(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new Qt({ndim:this.dims.length+1})]}computeOutputShape(e){e=ft(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return ot(Be(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};By.className="Permute";ae.registerClass(By);var Vy=class extends Je{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Be(e),r=-1;return Gu(wi(n,this.maskValue),r)}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Be(e),r=-1,a=!0,s=Gu(wi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Vy.className="Masking";ae.registerClass(Vy);var Uy=class extends Je{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let 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extends Je{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new Pe}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new V("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[ft(e)]),e=e,e.length<2)throw new V(`A merge layer should be called on an Array of at least 2 inputs. 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e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Ky.className="Concatenate";ae.registerClass(Ky);function Hc(e,t){for(;e<0;)e+=t;return e}function Pne(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new Pe("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new Pe("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return W(()=>{let i;if(r>a){i=r-a;let l=[];for(let u=0;u<i;++u)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let u=0;u<i;++u)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,u=s[1]===t.shape.length-1;o=e.matMul(t,l,u)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let u=[];for(let c=l;c<l+i;++c)u.push(c);o=o.squeeze(u)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var Zy=class extends Li{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new Pe("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 V(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new V(`A \`Dot\` layer must be called on exactly 2 inputs, but 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Yy=class extends Je{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 W(()=>{this.invokeCallHook(e,t);let n=Be(e);return $c(()=>Lp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Yy.className="GaussianNoise";ae.registerClass(Yy);var Jy=class extends Je{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Be(e);return this.rate>0&&this.rate<1?$c(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Lp(n.shape,1,r))},()=>n,t.training||!1):n})}};Jy.className="GaussianDropout";ae.registerClass(Jy);var Qy=class extends Je{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Be(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return W(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return $c(()=>{let r=Be(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=Ha(Il(n),this.rate);o=Rc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,u=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(u)},()=>Be(e),t.training||!1)}return e})}};Qy.className="AlphaDropout";ae.registerClass(Qy);function jc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=mx(e,t,n,r,a,s);else if(e.rank===3)i=Ax(e,t,n,r,a,s);else if(e.rank===4)i=yx(e,t,n,r,a,s);else throw new Pe(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function Lne(e,t,n,r,a=.001){return W(()=>{let s=zd(e,r),i=s.mean,o=s.variance;return[jc(e,i,o,n,t,a),i,o]})}function Wne(e,t,n,r,a=.001){return W(()=>{let s=zd(e,r),i=s.mean,o=s.variance,l=[];for(let p of 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Je{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=_t(e.betaInitializer||"zeros"),this.gammaInitializer=_t(e.gammaInitializer||"ones"),this.movingMeanInitializer=_t(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=_t(e.movingVarianceInitializer||"ones"),this.betaConstraint=qt(e.betaConstraint),this.gammaConstraint=qt(e.gammaConstraint),this.betaRegularizer=vt(e.betaRegularizer),this.gammaRegularizer=vt(e.gammaRegularizer)}build(e){e=ft(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new V(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Qt({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return W(()=>{let n=t.training==null?!1:t.training,r=Be(e),a=r.shape,s=a.length,i=Cr(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=Ri(1,s);l[o]=a[o];let u=i.slice();u.sort();let c=!v.arraysEqual(u,Cr(0,s).slice(0,s-1)),h=()=>{if(c){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return jc(r,A,y,g,w,this.epsilon)}else return jc(r,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return h();let[d,p,f]=Bne(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{W(()=>{let w=1-g,_=A.read(),b=_.sub(y).mul(w);A.write(_.sub(b))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Et(this.betaInitializer),gammaInitializer:Et(this.gammaInitializer),movingMeanInitializer:Et(this.movingMeanInitializer),movingVarianceInitializer:Et(this.movingVarianceInitializer),betaRegularizer:mt(this.betaRegularizer),gammaRegularizer:mt(this.gammaRegularizer),betaConstraint:Gt(this.betaConstraint),gammaConstraint:Gt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};eg.className="BatchNormalization";ae.registerClass(eg);var tg=class extends Je{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=_t(e.betaInitializer||"zeros"),this.gammaInitializer=_t(e.gammaInitializer||"ones"),this.betaRegularizer=vt(e.betaRegularizer),this.gammaRegularizer=vt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=ft(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Za(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Be(e),r=n.shape,a=r.length;return W(()=>{let s=!0,{mean:i,variance:o}=zd(n,this.axis,s),l=Ri(1,a);for(let f of this.axis)l[f]=r[f];let u=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,c=u(this.gamma.read()),h=u(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),c=c.tile(p),h=h.tile(p),jc(n,i,o,h,c,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Et(this.betaInitializer),gammaInitializer:Et(this.gammaInitializer),betaRegularizer:mt(this.betaRegularizer),gammaRegularizer:mt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};tg.className="LayerNormalization";ae.registerClass(tg);function Vne(e,t,n){return W(()=>{if(e.rank!==4)throw new V(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new V("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=Tr()),n!=="channelsLast"&&n!=="channelsFirst")throw new V(`Unknown data format: ${n}. 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length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Qt({ndim:4})]}computeOutputShape(e){e=ft(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return W(()=>Vne(Be(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};ng.className="ZeroPadding2D";ae.registerClass(ng);function f0(e,t,n,r,a,s){return W(()=>{Mt(a),u7(s),rr(r),n==null&&(n=[1,1]),r==null&&(r="valid"),a==null&&(a=Tr()),s==null&&(s="max"),e=ky(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=nc(e,t,n,o):i=Ku(e,t,n,o),a==="channelsFirst"&&(i=ot(i,[0,3,1,2])),i})}function Iv(e,t,n,r,a,s){return W(()=>{Mt(a),u7(s),rr(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=Tr()),s==null&&(s="max"),e=xv(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=km(e,t,n,o):i=cm(e,t,n,o),a==="channelsFirst"&&(i=ot(i,[0,4,1,2,3])),i})}var Nv=class extends Je{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new V(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Jt(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new V(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,rr(this.padding),this.inputSpec=[new Qt({ndim:3})]}computeOutputShape(e){e=ft(e);let t=Mr(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return W(()=>{this.invokeCallHook(e,t),e=Fc(Be(e),2);let n=this.poolingFunction(Be(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return ja(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},rg=class extends Nv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),f0(e,t,n,r,a,"max")}};rg.className="MaxPooling1D";ae.registerClass(rg);var ag=class extends Nv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),f0(e,t,n,r,a,"avg")}};ag.className="AveragePooling1D";ae.registerClass(ag);var Sv=class extends Je{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new V(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Jt(this.poolSize,"poolSize"),Jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Mt(this.dataFormat),rr(this.padding),this.inputSpec=[new Qt({ndim:4})]}computeOutputShape(e){e=ft(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Mr(t,this.poolSize[0],this.padding,this.strides[0]),n=Mr(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return W(()=>(this.invokeCallHook(e,t),this.poolingFunction(Be(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},sg=class extends Sv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),f0(e,t,n,r,a,"max")}};sg.className="MaxPooling2D";ae.registerClass(sg);var ig=class extends Sv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),f0(e,t,n,r,a,"avg")}};ig.className="AveragePooling2D";ae.registerClass(ig);var Tv=class extends Je{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new V(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Jt(this.poolSize,"poolSize"),Jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Mt(this.dataFormat),rr(this.padding),this.inputSpec=[new Qt({ndim:5})]}computeOutputShape(e){e=ft(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Mr(t,this.poolSize[0],this.padding,this.strides[0]),n=Mr(n,this.poolSize[1],this.padding,this.strides[1]),r=Mr(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return W(()=>(this.invokeCallHook(e,t),this.poolingFunction(Be(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},og=class extends Tv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),Iv(e,t,n,r,a,"max")}};og.className="MaxPooling3D";ae.registerClass(og);var lg=class extends Tv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),Iv(e,t,n,r,a,"avg")}};lg.className="AveragePooling3D";ae.registerClass(lg);var Ev=class extends Je{constructor(e){super(e);this.inputSpec=[new Qt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Pe}},ug=class extends Ev{constructor(e){super(e||{})}call(e,t){return W(()=>{let n=Be(e);return Tt(n,1)})}};ug.className="GlobalAveragePooling1D";ae.registerClass(ug);var cg=class extends Ev{constructor(e){super(e||{})}call(e,t){return W(()=>{let n=Be(e);return er(n,1)})}};cg.className="GlobalMaxPooling1D";ae.registerClass(cg);var Cv=class extends Je{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Mt(this.dataFormat),this.inputSpec=[new Qt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Pe}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},hg=class extends Cv{call(e,t){return W(()=>{let n=Be(e);return this.dataFormat==="channelsLast"?Tt(n,[1,2]):Tt(n,[2,3])})}};hg.className="GlobalAveragePooling2D";ae.registerClass(hg);var dg=class extends Cv{call(e,t){return W(()=>{let n=Be(e);return this.dataFormat==="channelsLast"?er(n,[1,2]):er(n,[2,3])})}};dg.className="GlobalMaxPooling2D";ae.registerClass(dg);var Rv=class extends Je{constructor(e){super(e);this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let r=t.layer,a=Fr(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},pg=class extends Rv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=ft(e),e.length<3)throw new V(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=ft(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return W(()=>(e=Be(e),vv((n,r)=>[Be(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};pg.className="TimeDistributed";ae.registerClass(pg);function Une(e){Mi(tee,"BidirectionalMergeMode",e)}var Hne="concat",fg=class extends Rv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Fr(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=Fr(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?Hne:e.mergeMode,Une(this.mergeMode),e.weights)throw new Pe("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Fn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=_v(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new V("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let u=n.map(c=>new Qt({shape:c.shape}));this.forwardLayer.stateSpec=u.slice(0,l/2),this.backwardLayer.stateSpec=u.slice(l/2),i.push(...u)}if(r!=null)throw new Pe("Support for constants in Bidirectional layers is not implemented yet.");let o=s[0]instanceof Rr;for(let l of s)if(l instanceof Rr!==o)throw new V("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(o){let l=[e].concat(s),u=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=u;let h=super.apply(l,t);return this.inputSpec=c,h}else return super.apply(e,t)}call(e,t){return W(()=>{let n=t.initialState,r,a;if(n==null)r=this.forwardLayer.call(e,t),a=this.backwardLayer.call(e,t);else{let o=n.slice(0,n.length/2),l=n.slice(n.length/2);r=this.forwardLayer.call(e,Object.assign(t,{initialState:o})),a=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let s;this.returnState&&(Array.isArray(r)&&(s=r.slice(1).concat(a.slice(1))),r=r[0],a=a[0]),this.returnSequences&&(a=Ln(a,1));let i;return this.mergeMode==="concat"?i=BA([r,a]):this.mergeMode==="sum"?i=ie(r,a):this.mergeMode==="ave"?i=P(.5,ie(r,a)):this.mergeMode==="mul"?i=P(r,a):this.mergeMode==null&&(i=[r,a]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){$i(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),$i(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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Hence the notion of "output shape" is ill-defined for the layer.`)}countParams(){if(!this.built)throw new Er(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return Yp(this.weights)}build(e){this.built=!0}getWeights(e=!1){return ey(e?this.trainableWeights:this.weights)}setWeights(e){L(()=>{let t=this.weights;if(t.length!==e.length)throw new W(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. 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this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};Zl.className="Sequential";ae.registerClass(Zl);function wne(e){return new ga(e)}function bne(e){return new Zl(e)}function _ne(e,t){return t==null&&(t={}),gne(e,t)}function _7(e){return R7(e)}function vne(e,t){yr.registerCallbackConstructor(e,t)}var Un=class extends ae.Serializable{getConfig(){return{}}},sv=class extends Un{apply(e,t=1){return tee(e,t)}};sv.className="elu";ae.registerClass(sv);var iv=class extends Un{apply(e){return Ud(e)}};iv.className="selu";ae.registerClass(iv);var ov=class extends Un{apply(e){return Hr(e)}};ov.className="relu";ae.registerClass(ov);var lv=class extends Un{apply(e){return L(()=>kl(6,Hr(e)))}};lv.className="relu6";ae.registerClass(lv);var uv=class extends Un{apply(e){return e}};uv.className="linear";ae.registerClass(uv);var cv=class extends Un{apply(e){return 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t.className=e,t.config={},Ay(t)}else return e instanceof Un?e:Ay(e)}function yy(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var yv=class extends ae.Serializable{},Bc=class extends yv{constructor(e){super();yy(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return L(()=>{let t=Ot([1]);return this.hasL1&&(t=ie(t,Fe(O(this.l1,Vt(e))))),this.hasL2&&(t=ie(t,Fe(O(this.l2,$c(e))))),t.asScalar()})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Bc.className="L1L2";ae.registerClass(Bc);function kne(e){return yy(e),new Bc({l1:e!=null?e.l1:null,l2:0})}function Ine(e){return yy(e),new Bc({l2:e!=null?e.l2:null,l1:0})}var gv={l1l2:"L1L2"};function ft(e){return RA(e)}function xv(e,t={}){return Ec(e,ae.SerializationMap.getMap().classNameMap,t,"regularizer")}function _t(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in gv?gv[e]:e,config:{}};return xv(t)}else return e instanceof yv?e:xv(e)}var gy=class extends Je{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Be(e);let n=Hr(e);return this.maxValue!=null&&(n=Sn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};gy.className="ReLU";ae.registerClass(gy);var xy=class extends Je{constructor(e){super(e==null?{}:e);this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Be(e);return tc(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};xy.className="LeakyReLU";ae.registerClass(xy);var wy=class extends Je{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=bt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=_t(e.alphaRegularizer),this.alphaConstraint=qt(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new W(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=pt(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let r of this.sharedAxes)t[r-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let r=1;r<e.length;++r)n[r]=e[r];this.inputSpec=[new Qt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Be(e),sc(e,this.alpha.read())}getConfig(){let e={alphaInitializer:Et(this.alphaInitializer),alphaRegularizer:ft(this.alphaRegularizer),alphaConstraint:Gt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};wy.className="PReLU";ae.registerClass(wy);var by=class extends Je{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new Pe(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Be(e);return wl(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};by.className="ELU";ae.registerClass(by);var _y=class extends Je{constructor(e){super(e==null?{}:e);this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=Be(e);return n.mul(Fc(n.greater(this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};_y.className="ThresholdedReLU";ae.registerClass(_y);var vy=class extends Je{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new my().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Be(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}};vy.className="Softmax";ae.registerClass(vy);function Yl(e,t,n){if(typeof e=="number")return Ri(e,t);if(e.length!==t)throw new W(`The ${n} argument must be an integer or tuple of ${t} integers. 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instead`);if(s==="channelsFirst"&&(e=it(e,[0,2,1])),a==="causal")throw new Pe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=Td(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Yr(o,n)),o})}function bv(e,t,n,r=[1,1],a="valid",s,i,o=null){return L(()=>{if(s==null&&(s=Tr()),Mt(s),e.rank!==3&&e.rank!==4)throw new W(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new W(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=ky(e,s);if(a==="causal")throw new Pe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Ga.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=it(l,[0,3,1,2])),l})}function Sne(e,t,n,r=[1,1,1],a="valid",s,i){return L(()=>{if(s==null&&(s=Tr()),Mt(s),e.rank!==4&&e.rank!==5)throw new W(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new W(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=wv(e,s);if(a==="causal")throw new Pe("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=pm(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Yr(o,n)),s==="channelsFirst"&&(o=it(o,[0,4,1,2,3])),o})}var Iy=class extends Je{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Iy.verifyArgs(t),this.rank=e,Jt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Pe(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Yl(t.kernelSize,e,"kernelSize"),this.strides=Yl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,rr(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Mt(this.dataFormat),this.activation=ts(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=bt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=qt(t.biasConstraint),this.biasRegularizer=_t(t.biasRegularizer),this.activityRegularizer=_t(t.activityRegularizer),this.dilationRate=Yl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new W(`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 W(`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 W(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Kr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!MA(e.kernelSize,"number",1,3))throw new W(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:es(this.activation),useBias:this.useBias,biasInitializer:Et(this.biasInitializer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),biasConstraint:Gt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Vc=class extends Iy{constructor(e,t){super(e,t);this.kernel=null,Vc.verifyArgs(t),this.filters=t.filters,Jt(this.filters,"filters"),this.kernelInitializer=bt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=qt(t.kernelConstraint),this.kernelRegularizer=_t(t.kernelRegularizer)}build(e){e=pt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new W(`The channel dimension of the input should be defined. 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Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Qt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return L(()=>{let n=Be(e);if(n.shape.length!==4)throw new W(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],u=this.kernelSize[0],c=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=o0(o,h,u,this.padding),f=o0(l,d,c,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=it(n,[0,2,3,1]));let A=Ed(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=it(A,[0,3,1,2])),this.bias!=null&&(A=Yr(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=pt(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=o0(t[r],o,s,this.padding),t[a]=o0(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Ny.className="Conv2DTranspose";ae.registerClass(Ny);var _v=class extends Vc{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 W("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new W("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 W(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=bt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=_t(t.depthwiseRegularizer),this.depthwiseConstraint=qt(t.depthwiseConstraint),this.pointwiseInitializer=bt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=_t(t.pointwiseRegularizer),this.pointwiseConstraint=qt(t.pointwiseConstraint)}build(e){if(e=pt(e),e.length<this.rank+2)throw new W(`Inputs to SeparableConv${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 W(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Qt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return L(()=>{e=Be(e);let n;if(this.rank===1)throw new Pe("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=it(e,[0,2,3,1])),n=Rm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Yr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=it(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=Et(this.depthwiseInitializer),e.pointwiseInitializer=Et(this.pointwiseInitializer),e.depthwiseRegularizer=ft(this.depthwiseRegularizer),e.pointwiseRegularizer=ft(this.pointwiseRegularizer),e.depthwiseConstraint=Gt(this.depthwiseConstraint),e.pointwiseConstraint=Gt(this.pointwiseConstraint),e}};_v.className="SeparableConv";var Sy=class extends _v{constructor(e){super(2,e)}};Sy.className="SeparableConv2D";ae.registerClass(Sy);var u0=class extends Vc{constructor(e){super(1,e);u0.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"&&!MA(e.kernelSize,"number",1,1))throw new W(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};u0.className="Conv1D";ae.registerClass(u0);var Ty=class extends Je{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 L(()=>{if(e=Be(e),this.dataFormat==="channelsLast"){let n=Lp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Lp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Lp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Lp(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}};Ty.className="Cropping2D";ae.registerClass(Ty);var Ey=class extends Je{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,Mt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,XQ(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 L(()=>{let n=Be(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=it(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return it(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Ey.className="UpSampling2D";ae.registerClass(Ey);function Tne(e,t,n=[1,1],r="valid",a,s){return L(()=>{a==null&&(a=Tr()),Mt(a);let i=ky(e,a);if(e.rank!==4)throw new W(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new W(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=xl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=it(i,[0,3,1,2])),i})}var Cy=class extends Iy{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=bt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=qt(e.depthwiseConstraint),this.depthwiseRegularizer=_t(e.depthwiseRegularizer)}build(e){if(e=pt(e),e.length<4)throw new W(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new W(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${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 L(()=>{e=Be(e);let n=Tne(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Yr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=pt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Mr(t,this.kernelSize[0],this.padding,this.strides[0]),s=Mr(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Et(this.depthwiseInitializer),e.depthwiseRegularizer=ft(this.depthwiseRegularizer),e.depthwiseConstraint=Gt(this.depthwiseRegularizer),e}};Cy.className="DepthwiseConv2D";ae.registerClass(Cy);function vv(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new W("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function kv(e,t,n,r=!1,a,s,i=!1,o=!1){return L(()=>{let l=t.shape.length;if(l<3)throw new W(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Cr(2,l));if(t=it(t,u),s!=null)throw new Pe("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=mn(a,-1)),a=it(a,u)),r&&(t=Ln(t,0),a!=null&&(a=Ln(a,0)));let c=[],h,d=n,p=t.shape[0],f=pr(t),m;a!=null&&(m=pr(a));for(let y=0;y<p;++y){let g=f[y],w=L(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let b=L(()=>{let _=m[y],x=Pn(_).sub(_),N=w[0].mul(_).add(d[0].mul(x)),T=d.map((E,M)=>w[1][M].mul(_).add(E.mul(x)));return{output:N,newStates:T}});h=b.output,d=b.newStates}o&&c.push(h)}let A;return o&&(A=An(c,1)),[h,A,d]})}var Jr=class extends Je{constructor(e){super(e);let t;if(e.cell==null)throw new W("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new c0({cells:e.cell}):t=e.cell,t.stateSize==null)throw new W("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new Qt({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Cr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){QA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return L(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new Pe("Constants support is not implemented in RNN yet.");QA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Qt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new Pe("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new W(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Qt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){L(()=>{if(!this.stateful)throw new Aa("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new W("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=>Ot([n,r])):this.states_=[Ot([n,this.cell.stateSize])];else if(e==null)Re(this.states_),this.keptStates!=null&&(Re(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Ot([n,r])):this.states_[0]=Ot([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new W(`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()):Re(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new W(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Zt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=vv(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Qt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof Rr){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let c=super.apply(o,t);return this.inputSpec=u,c}else return super.apply(e,t)}call(e,t){return L(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Be(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new W(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=kv((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],c=o[2];this.stateful&&this.resetStates(c,r);let h=this.returnSequences?u:l;return this.returnState?[h].concat(c):h})}getInitialState(e){return L(()=>{let t=Ot(e.shape);return t=Fe(t,[1,2]),t=Mc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?LA(t,[1,n]):t):this.cell.stateSize>1?[LA(t,[1,this.cell.stateSize])]:[t]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){let e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(t.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===Jr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=Fr(r,n);return new e(Object.assign(t,{cell:a}))}};Jr.className="RNN";ae.registerClass(Jr);var Oc=class extends Je{},h0=class extends Oc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Jt(this.units,"units"),this.activation=ts(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=bt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=bt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=bt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=_t(e.kernelRegularizer),this.recurrentRegularizer=_t(e.recurrentRegularizer),this.biasRegularizer=_t(e.biasRegularizer),this.kernelConstraint=qt(e.kernelConstraint),this.recurrentConstraint=qt(e.recurrentConstraint),this.biasConstraint=qt(e.biasConstraint),this.dropout=Gl([1,Ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Gl([1,Ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=pt(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 L(()=>{if(e=e,e.length!==2)throw new W(`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=ns({ones:()=>Pn(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ns({ones:()=>Pn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Zr(O(e,s),this.kernel.read()):a=Zr(e,this.kernel.read()),this.bias!=null&&(a=Yr(a,this.bias.read())),i!=null&&(n=O(n,i));let o=ie(a,Zr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:es(this.activation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),recurrentInitializer:Et(this.recurrentInitializer),biasInitializer:Et(this.biasInitializer),kernelRegularizer:ft(this.kernelRegularizer),recurrentRegularizer:ft(this.recurrentRegularizer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),kernelConstraint:Gt(this.kernelConstraint),recurrentConstraint:Gt(this.recurrentConstraint),biasConstraint:Gt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};h0.className="SimpleRNNCell";ae.registerClass(h0);var Ry=class extends Jr{constructor(e){e.cell=new h0(e),super(e)}call(e,t){return L(()=>{this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};Ry.className="SimpleRNN";ae.registerClass(Ry);var d0=class extends Oc{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 W("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Jt(this.units,"units"),this.activation=ts(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ts(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=bt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=bt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=bt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=_t(e.kernelRegularizer),this.recurrentRegularizer=_t(e.recurrentRegularizer),this.biasRegularizer=_t(e.biasRegularizer),this.kernelConstraint=qt(e.kernelConstraint),this.recurrentConstraint=qt(e.recurrentConstraint),this.biasConstraint=qt(e.biasConstraint),this.dropout=Gl([1,Ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Gl([1,Ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=pt(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 L(()=>{if(e=e,e.length!==2)throw new W(`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=ns({ones:()=>Pn(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ns({ones:()=>Pn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=O(e,a[0]));let u=Zr(e,this.kernel.read());this.useBias&&(u=Yr(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=O(r,s[0]));let c=this.recurrentKernel.read(),[h,d]=jt(c,[2*this.units,this.units],c.rank-1),p=Zr(r,h),[f,m,A]=jt(u,3,u.rank-1),[y,g]=jt(p,2,p.rank-1);i=this.recurrentActivation.apply(ie(f,y)),o=this.recurrentActivation.apply(ie(m,g));let w=Zr(O(o,r),d);l=this.activation.apply(ie(A,w));let b=ie(O(i,r),O(ie(1,St(i)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:es(this.activation),recurrentActivation:es(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),recurrentInitializer:Et(this.recurrentInitializer),biasInitializer:Et(this.biasInitializer),kernelRegularizer:ft(this.kernelRegularizer),recurrentRegularizer:ft(this.recurrentRegularizer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),kernelConstraint:Gt(this.kernelConstraint),recurrentConstraint:Gt(this.recurrentConstraint),biasConstraint:Gt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};d0.className="GRUCell";ae.registerClass(d0);var Fy=class extends Jr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new d0(e),super(e)}call(e,t){return L(()=>{this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Fy.className="GRU";ae.registerClass(Fy);var jc=class extends Oc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Jt(this.units,"units"),this.activation=ts(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ts(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=bt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=bt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=bt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=_t(e.kernelRegularizer),this.recurrentRegularizer=_t(e.recurrentRegularizer),this.biasRegularizer=_t(e.biasRegularizer),this.kernelConstraint=qt(e.kernelConstraint),this.recurrentConstraint=qt(e.recurrentConstraint),this.biasConstraint=qt(e.biasConstraint),this.dropout=Gl([1,Ja([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Gl([1,Ja([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=pt(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends Ar{apply(i,o){let l=a.apply([s]),u=new Bp().apply([s]),c=a.apply([s*2]);return A7(A7(l,u),c)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return L(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new W(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ns({ones:()=>Pn(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ns({ones:()=>Pn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,c;0<this.dropout&&this.dropout<1&&(e=O(e,s[0]));let h=Zr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=O(r,i[0])),h=ie(h,Zr(r,this.recurrentKernel.read())),this.useBias&&(h=Yr(h,this.bias.read()));let[d,p,f,m]=jt(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),u=ie(O(l,a),O(o,this.activation.apply(f))),c=this.recurrentActivation.apply(m);let A=O(c,this.activation.apply(u));return[A,A,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:es(this.activation),recurrentActivation:es(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),recurrentInitializer:Et(this.recurrentInitializer),biasInitializer:Et(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:ft(this.kernelRegularizer),recurrentRegularizer:ft(this.recurrentRegularizer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),kernelConstraint:Gt(this.kernelConstraint),recurrentConstraint:Gt(this.recurrentConstraint),biasConstraint:Gt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};jc.className="LSTMCell";ae.registerClass(jc);var My=class extends Jr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new jc(e),super(e)}call(e,t){return L(()=>{this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};My.className="LSTM";ae.registerClass(My);var c0=class extends Oc{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return L(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){QA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{$i(`RNNCell_${r}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(Fr(a,n));return new e({cells:r})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return ey(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}ty(t)}};c0.className="StackedRNNCells";ae.registerClass(c0);function ns(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>g7(t(),n),i=()=>Dc(s,t,r);return!a||a<=1?Zt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Zt(o.clone()))}var Ene=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},Iv=class extends Jr{constructor(e){if(e.unroll)throw new Pe("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Pe("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Qt({ndim:5})]}call(e,t){return L(()=>{if(this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new W("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return L(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Ot(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){L(()=>{if(!this.stateful)throw new Aa("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new W("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ot(a)):this.states_=[Ot(a)];else if(e==null)Re(this.states_),this.keptStates!=null&&(Re(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ot(a)):this.states_[0]=Ot(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new W(`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()):Re(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new W(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Zt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],u=e[o?4:3],c=Mr(l,r[0],a,s[0],i[0]),h=Mr(u,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,c,h]:[c,h,n]]}};Iv.className="ConvRNN2D";var p0=class extends jc{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Jt(this.filters,"filters"),this.kernelSize=Yl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Jt(o,"kernelSize")),this.strides=Yl(r||1,2,"strides"),this.strides.forEach(o=>Jt(o,"strides")),this.padding=a||"valid",rr(this.padding),this.dataFormat=s||"channelsLast",Mt(this.dataFormat),this.dilationRate=Yl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Jt(o,"dilationRate"))}build(e){var t;e=pt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new W(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;o=new(t=class extends Ar{apply(c,h){let d=l.apply([u]),p=jr([u]),f=l.apply([u*2]);return BA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return L(()=>{if(e.length!==3)throw new W(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ns({ones:()=>Pn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,se,ne)=>!se||!se[ne]?Y:O(se[ne],Y),u=l(r,o,0),c=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ns({ones:()=>Pn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,b,_,x]=jt(this.kernel.read(),i,g),[N,T,E,M]=this.useBias?jt(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,w,N,this.padding),c=this.inputConv(c,b,T,this.padding),h=this.inputConv(h,_,E,this.padding),d=this.inputConv(d,x,M,this.padding);let[z,B,V,U]=jt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,z),m=this.recurrentConv(m,B),A=this.recurrentConv(A,V),y=this.recurrentConv(y,U);let j=this.recurrentActivation.apply(ie(u,f)),X=this.recurrentActivation.apply(ie(c,m)),G=ie(O(X,s),O(j,this.activation.apply(ie(h,A)))),ee=O(this.recurrentActivation.apply(ie(d,y)),this.activation.apply(G));return[ee,ee,G]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=Ene(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=ca(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Yr(a,n,this.dataFormat):a}recurrentConv(e,t){return ca(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};p0.className="ConvLSTM2DCell";ae.registerClass(p0);var $y=class extends Iv{constructor(e){let t=new p0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};$y.className="ConvLSTM2D";ae.registerClass($y);var f0=class extends Je{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 L(()=>{this.invokeCallHook(e,t);let n=Be(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Dc(()=>g7(n,this.rate,a,this.seed),()=>n,r)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};f0.className="Dropout";ae.registerClass(f0);var Dy=class extends f0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Dy.className="SpatialDropout1D";ae.registerClass(Dy);var Oy=class extends Je{constructor(e){super(e);if(this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,Jt(this.units,"units"),this.activation=ts(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=bt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=bt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=qt(e.kernelConstraint),this.biasConstraint=qt(e.biasConstraint),this.kernelRegularizer=_t(e.kernelRegularizer),this.biasRegularizer=_t(e.biasRegularizer),this.activityRegularizer=_t(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=pt(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=pt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Be(e),r=i7(this.activation.getClassName()),a;return r!=null?a=Zr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Zr(n,this.kernel.read()),this.bias!=null&&(a=Yr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:es(this.activation),useBias:this.useBias,kernelInitializer:Et(this.kernelInitializer),biasInitializer:Et(this.biasInitializer),kernelRegularizer:ft(this.kernelRegularizer),biasRegularizer:ft(this.biasRegularizer),activityRegularizer:ft(this.activityRegularizer),kernelConstraint:Gt(this.kernelConstraint),biasConstraint:Gt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Oy.className="Dense";ae.registerClass(Oy);var zy=class extends Je{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=pt(e);for(let t of e.slice(1))if(t==null)throw new W(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],Ya(e,1)]}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Be(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a<n.rank;++a)r.push(a);r.push(1),n=n.transpose(r)}return eee(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};zy.className="Flatten";ae.registerClass(zy);var Py=class extends Je{constructor(e){super(e);this.supportsMasking=!0,this.activation=ts(e.activation)}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Be(e);return this.activation.apply(n)})}getConfig(){let e={activation:es(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Py.className="Activation";ae.registerClass(Py);var Ly=class extends Je{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return L(()=>(e=Be(e),JQ(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Ly.className="RepeatVector";ae.registerClass(Ly);var Wy=class extends Je{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new W("Can only specifiy one unknown dimension.");else a*=l}let i=Ya(e);if(s!==null){if(a===0||i%a!=0)throw new W(n);r[s]=i/a}else if(i!==a)throw new W(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 L(()=>{this.invokeCallHook(e,t);let n=Be(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Wy.className="Reshape";ae.registerClass(Wy);var By=class extends Je{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=Cr(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new Qt({ndim:this.dims.length+1})]}computeOutputShape(e){e=pt(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return it(Be(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};By.className="Permute";ae.registerClass(By);var Vy=class extends Je{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Be(e),r=-1;return qu(wi(n,this.maskValue),r)}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Be(e),r=-1,a=!0,s=qu(wi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Vy.className="Masking";ae.registerClass(Vy);var Uy=class extends Je{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(At(e.inputLength))}this.inputDim=e.inputDim,Jt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Jt(this.outputDim,"outputDim"),this.embeddingsInitializer=bt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=_t(e.embeddingsRegularizer),this.activityRegularizer=_t(e.activityRegularizer),this.embeddingsConstraint=qt(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return L(()=>this.maskZero?(e=Be(e),wi(e,Xe(e))):null)}computeOutputShape(e){if(e=pt(e),this.inputLength==null)return[...e,this.outputDim];let t=At(this.inputLength);if(t.length!==e.length-1)throw new W(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new W(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Be(e);return n.dtype!=="int32"&&(n=Fc(n,"int32")),y7(this.embeddings.read(),n.as1D()).reshape(pt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Et(this.embeddingsInitializer),embeddingsRegularizer:ft(this.embeddingsRegularizer),activityRegularizer:ft(this.activityRegularizer),embeddingsConstraint:Gt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Uy.className="Embedding";ae.registerClass(Uy);var Li=class extends Je{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new Pe}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new W("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[pt(e)]),e=e,e.length<2)throw new W(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let a of e)a!=null&&a[0]!==null&&t.push(a[0]);if(t=Za(t),t.length>1)throw new W(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let a=1;a<e.length;++a){let s=e[a]==null?null:e[a].slice(1);n=this.computeElementwiseOpOutputShape(n,s)}let r=e.map(a=>a.length);e.indexOf(null)===-1&&Za(r).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return L(()=>{if(e=e,this.reshapeRequired){let n=[],r=e.map(a=>a.rank);if(r.indexOf(null)===-1){let a=Ja(r);for(let s of e){let i=s.rank;for(let o=0;o<a-i;++o)s=Mc(s,1);n.push(s)}return this.mergeFunction(n)}else{let a=!1;for(let o of e){let l=o.rank;if(l==null){let u=o.shape,c=u[0],h=u.slice(1).concat([c]),d=o.reshape([c].concat(Ya(u.slice(1))));d=it(d,[1,0]),d=d.reshape(h),n.push(d),a=!0}else if(l>1){let u=Cr(1,l).concat([0]);n.push(it(o,u)),a=!0}else n.push(o)}let s=this.mergeFunction(n),i=s.rank;if(a){if(i==null){let o=s.shape,l=o.length,u=o[l-1],c=[u].concat(o.slice(0,o.length-1));s=it(s.reshape([-1,u]),[1,0]).reshape(c)}else if(i>1){let o=[i-1].concat(Cr(0,i-1));s=it(s,o)}}return s}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);t=this.computeElementwiseOpOutputShape(t,a)}let n=[];for(let r of e)r!=null&&r[0]!==null&&n.push(r[0]);return n=Za(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return L(()=>{if(t==null)return null;if(!Array.isArray(t))throw new W("`mask` should be an Array");if(!Array.isArray(e))throw new W("`inputs` should be an Array");if(t.length!==e.length)throw new W(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(r=>r==null))return null;t=t.map(r=>r==null?r:mn(r,0));let n=t[0];for(let r=1;r<t.length-1;++r)n=dr(n,t[r]);return n})}},jy=class extends Li{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ie(t,e[n]);return t})}};jy.className="Add";ae.registerClass(jy);var Hy=class extends Li{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=O(t,e[n]);return t})}};Hy.className="Multiply";ae.registerClass(Hy);var Gy=class extends Li{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ie(t,e[n]);return O(1/e.length,t)})}};Gy.className="Average";ae.registerClass(Gy);var qy=class extends Li{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Ur(t,e[n]);return t})}};qy.className="Maximum";ae.registerClass(qy);var Xy=class extends Li{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=kl(t,e[n]);return t})}};Xy.className="Minimum";ae.registerClass(Xy);var Ky=class extends Li{constructor(e){super(e);this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new W("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let r of e)if(r!=null){t=!1;break}if(t)return;let n=[];for(let r=0;r<e.length;++r){let a=e[r].slice();a.splice(this.axis,1);let s=!1;for(let i of n)if(v.arraysEqual(i,a)){s=!0;break}s||n.push(a)}if(n.length>1)throw new W("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return L(()=>BA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new W("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),r=this.axis<0?n.length+this.axis:this.axis;for(let a of t.slice(1)){if(n[r]==null||a[r]==null){n[r]=null;break}n[r]+=a[r]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new W("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new W("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new W(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return L(()=>{let n=!0;if(t.forEach(s=>{if(s!=null){n=!1;return}}),n)return null;let r=[];for(let s=0;s<e.length;++s)t[s]==null?r.push(Pn(e[s]).asType("bool")):t[s].rank<e[s].rank?r.push(mn(t[s],-1)):r.push(t[s]);let a=ot(r,this.axis);return Nd(a,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Ky.className="Concatenate";ae.registerClass(Ky);function Hc(e,t){for(;e<0;)e+=t;return e}function Cne(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new Pe("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new Pe("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return L(()=>{let i;if(r>a){i=r-a;let l=[];for(let u=0;u<i;++u)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let u=0;u<i;++u)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,u=s[1]===t.shape.length-1;o=e.matMul(t,l,u)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let u=[];for(let c=l;c<l+i;++c)u.push(c);o=o.squeeze(u)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var Zy=class extends Li{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new Pe("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 W(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new W(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],r;return Array.isArray(this.axes)?r=this.axes.map((a,s)=>Hc(a,e[s].shape.length)):r=[Hc(this.axes,t.shape.length),Hc(this.axes,n.shape.length)],this.normalize&&(t=Qp(t,r[0]),n=Qp(n,r[1])),Cne(t,n,r)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Hc(this.axes,e.length),Hc(this.axes,t.length)],n}computeOutputShape(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new Pe("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);t.splice(r[0],1),n.splice(r[1],1),n.splice(0,1);let a=t.concat(n);return a.length===1&&a.push(1),a}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};Zy.className="Dot";ae.registerClass(Zy);var Yy=class extends Je{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 L(()=>{this.invokeCallHook(e,t);let n=Be(e);return Dc(()=>Wp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Yy.className="GaussianNoise";ae.registerClass(Yy);var Jy=class extends Je{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 L(()=>{this.invokeCallHook(e,t);let n=Be(e);return this.rate>0&&this.rate<1?Dc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Wp(n.shape,1,r))},()=>n,t.training||!1):n})}};Jy.className="GaussianDropout";ae.registerClass(Jy);var Qy=class extends Je{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Be(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return L(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Dc(()=>{let r=Be(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=ja(Il(n),this.rate);o=Fc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,u=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(u)},()=>Be(e),t.training||!1)}return e})}};Qy.className="AlphaDropout";ae.registerClass(Qy);function Gc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=Ax(e,t,n,r,a,s);else if(e.rank===3)i=yx(e,t,n,r,a,s);else if(e.rank===4)i=gx(e,t,n,r,a,s);else throw new Pe(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function Rne(e,t,n,r,a=.001){return L(()=>{let s=Pd(e,r),i=s.mean,o=s.variance;return[Gc(e,i,o,n,t,a),i,o]})}function Fne(e,t,n,r,a=.001){return L(()=>{let s=Pd(e,r),i=s.mean,o=s.variance,l=[];for(let p of Cr(0,e.rank))r.indexOf(p)!==-1?l.push(1):l.push(e.shape[p]);let u=i.reshape(l),c=o.reshape(l),h=t==null?null:t.reshape(l),d=n==null?null:n.reshape(l);return[Gc(e,u,c,d,h,a),i,o]})}function Mne(e,t,n,r,a=.001){return v.arraysEqual(r.slice().sort(),Cr(0,e.rank-1))?Rne(e,t,n,r,a):Fne(e,t,n,r,a)}var eg=class extends Je{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=bt(e.betaInitializer||"zeros"),this.gammaInitializer=bt(e.gammaInitializer||"ones"),this.movingMeanInitializer=bt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=bt(e.movingVarianceInitializer||"ones"),this.betaConstraint=qt(e.betaConstraint),this.gammaConstraint=qt(e.gammaConstraint),this.betaRegularizer=_t(e.betaRegularizer),this.gammaRegularizer=_t(e.gammaRegularizer)}build(e){e=pt(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new W(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Qt({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return L(()=>{let n=t.training==null?!1:t.training,r=Be(e),a=r.shape,s=a.length,i=Cr(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=Ri(1,s);l[o]=a[o];let u=i.slice();u.sort();let c=!v.arraysEqual(u,Cr(0,s).slice(0,s-1)),h=()=>{if(c){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return Gc(r,A,y,g,w,this.epsilon)}else return Gc(r,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return h();let[d,p,f]=Mne(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{L(()=>{let w=1-g,b=A.read(),_=b.sub(y).mul(w);A.write(b.sub(_))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Et(this.betaInitializer),gammaInitializer:Et(this.gammaInitializer),movingMeanInitializer:Et(this.movingMeanInitializer),movingVarianceInitializer:Et(this.movingVarianceInitializer),betaRegularizer:ft(this.betaRegularizer),gammaRegularizer:ft(this.gammaRegularizer),betaConstraint:Gt(this.betaConstraint),gammaConstraint:Gt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};eg.className="BatchNormalization";ae.registerClass(eg);var tg=class extends Je{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=bt(e.betaInitializer||"zeros"),this.gammaInitializer=bt(e.gammaInitializer||"ones"),this.betaRegularizer=_t(e.betaRegularizer),this.gammaRegularizer=_t(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=pt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Za(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Be(e),r=n.shape,a=r.length;return L(()=>{let s=!0,{mean:i,variance:o}=Pd(n,this.axis,s),l=Ri(1,a);for(let f of this.axis)l[f]=r[f];let u=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,c=u(this.gamma.read()),h=u(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),c=c.tile(p),h=h.tile(p),Gc(n,i,o,h,c,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Et(this.betaInitializer),gammaInitializer:Et(this.gammaInitializer),betaRegularizer:ft(this.betaRegularizer),gammaRegularizer:ft(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};tg.className="LayerNormalization";ae.registerClass(tg);function $ne(e,t,n){return L(()=>{if(e.rank!==4)throw new W(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new W("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=Tr()),n!=="channelsLast"&&n!=="channelsFirst")throw new W(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let r;return n==="channelsFirst"?r=[[0,0],[0,0],t[0],t[1]]:r=[[0,0],t[0],t[1],[0,0]],ha(e,r)})}var ng=class extends Je{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?Tr():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new W(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new W(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new W(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Qt({ndim:4})]}computeOutputShape(e){e=pt(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return L(()=>$ne(Be(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};ng.className="ZeroPadding2D";ae.registerClass(ng);function m0(e,t,n,r,a,s){return L(()=>{Mt(a),c7(s),rr(r),n==null&&(n=[1,1]),r==null&&(r="valid"),a==null&&(a=Tr()),s==null&&(s="max"),e=ky(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=rc(e,t,n,o):i=Zu(e,t,n,o),a==="channelsFirst"&&(i=it(i,[0,3,1,2])),i})}function Nv(e,t,n,r,a,s){return L(()=>{Mt(a),c7(s),rr(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=Tr()),s==null&&(s="max"),e=wv(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=km(e,t,n,o):i=cm(e,t,n,o),a==="channelsFirst"&&(i=it(i,[0,4,1,2,3])),i})}var Sv=class extends Je{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new W(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Jt(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new W(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,rr(this.padding),this.inputSpec=[new Qt({ndim:3})]}computeOutputShape(e){e=pt(e);let t=Mr(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return L(()=>{this.invokeCallHook(e,t),e=Mc(Be(e),2);let n=this.poolingFunction(Be(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Ha(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},rg=class extends Sv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),m0(e,t,n,r,a,"max")}};rg.className="MaxPooling1D";ae.registerClass(rg);var ag=class extends Sv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),m0(e,t,n,r,a,"avg")}};ag.className="AveragePooling1D";ae.registerClass(ag);var Tv=class extends Je{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new W(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Jt(this.poolSize,"poolSize"),Jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Mt(this.dataFormat),rr(this.padding),this.inputSpec=[new Qt({ndim:4})]}computeOutputShape(e){e=pt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Mr(t,this.poolSize[0],this.padding,this.strides[0]),n=Mr(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return L(()=>(this.invokeCallHook(e,t),this.poolingFunction(Be(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},sg=class extends Tv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),m0(e,t,n,r,a,"max")}};sg.className="MaxPooling2D";ae.registerClass(sg);var ig=class extends Tv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),m0(e,t,n,r,a,"avg")}};ig.className="AveragePooling2D";ae.registerClass(ig);var Ev=class extends Je{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new W(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Jt(this.poolSize,"poolSize"),Jt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Mt(this.dataFormat),rr(this.padding),this.inputSpec=[new Qt({ndim:5})]}computeOutputShape(e){e=pt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Mr(t,this.poolSize[0],this.padding,this.strides[0]),n=Mr(n,this.poolSize[1],this.padding,this.strides[1]),r=Mr(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return L(()=>(this.invokeCallHook(e,t),this.poolingFunction(Be(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},og=class extends Ev{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),Nv(e,t,n,r,a,"max")}};og.className="MaxPooling3D";ae.registerClass(og);var lg=class extends Ev{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Mt(a),rr(r),Nv(e,t,n,r,a,"avg")}};lg.className="AveragePooling3D";ae.registerClass(lg);var Cv=class extends Je{constructor(e){super(e);this.inputSpec=[new Qt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Pe}},ug=class extends Cv{constructor(e){super(e||{})}call(e,t){return L(()=>{let n=Be(e);return Tt(n,1)})}};ug.className="GlobalAveragePooling1D";ae.registerClass(ug);var cg=class extends Cv{constructor(e){super(e||{})}call(e,t){return L(()=>{let n=Be(e);return er(n,1)})}};cg.className="GlobalMaxPooling1D";ae.registerClass(cg);var Rv=class extends Je{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Mt(this.dataFormat),this.inputSpec=[new Qt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Pe}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},hg=class extends Rv{call(e,t){return L(()=>{let n=Be(e);return this.dataFormat==="channelsLast"?Tt(n,[1,2]):Tt(n,[2,3])})}};hg.className="GlobalAveragePooling2D";ae.registerClass(hg);var dg=class extends Rv{call(e,t){return L(()=>{let n=Be(e);return this.dataFormat==="channelsLast"?er(n,[1,2]):er(n,[2,3])})}};dg.className="GlobalMaxPooling2D";ae.registerClass(dg);var Fv=class extends Je{constructor(e){super(e);this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let r=t.layer,a=Fr(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},pg=class extends Fv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=pt(e),e.length<3)throw new W(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=pt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return L(()=>(e=Be(e),kv((n,r)=>[Be(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};pg.className="TimeDistributed";ae.registerClass(pg);function Dne(e){Mi(qQ,"BidirectionalMergeMode",e)}var One="concat",fg=class extends Fv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Fr(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=Fr(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?One:e.mergeMode,Dne(this.mergeMode),e.weights)throw new Pe("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Fn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=vv(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new W("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let u=n.map(c=>new Qt({shape:c.shape}));this.forwardLayer.stateSpec=u.slice(0,l/2),this.backwardLayer.stateSpec=u.slice(l/2),i.push(...u)}if(r!=null)throw new Pe("Support for constants in Bidirectional layers is not implemented yet.");let o=s[0]instanceof Rr;for(let l of s)if(l instanceof Rr!==o)throw new W("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(o){let l=[e].concat(s),u=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=u;let h=super.apply(l,t);return this.inputSpec=c,h}else return super.apply(e,t)}call(e,t){return L(()=>{let n=t.initialState,r,a;if(n==null)r=this.forwardLayer.call(e,t),a=this.backwardLayer.call(e,t);else{let o=n.slice(0,n.length/2),l=n.slice(n.length/2);r=this.forwardLayer.call(e,Object.assign(t,{initialState:o})),a=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let s;this.returnState&&(Array.isArray(r)&&(s=r.slice(1).concat(a.slice(1))),r=r[0],a=a[0]),this.returnSequences&&(a=Ln(a,1));let i;return this.mergeMode==="concat"?i=BA([r,a]):this.mergeMode==="sum"?i=ie(r,a):this.mergeMode==="ave"?i=O(.5,ie(r,a)):this.mergeMode==="mul"?i=O(r,a):this.mergeMode==null&&(i=[r,a]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){$i(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),$i(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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+        ${n}, and tensor's shape is: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);let a=n===0?0:t.size/n,s=[];L(()=>{t=H(t,[1,n,a]);for(let o=0;o<e.length;++o){let l=o===0?0:r[o-1],u=[0,l,0],c=[1,e[o],a];s[o]=H($e(t,u,c),this.elementShape)}return s});let i=[];for(let o=0;o<e.length;o++)i[o]=o;this.writeMany(i,s)}},Xc=class{constructor(e,t,n,r=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,e!=null&&e.forEach(a=>{if(n!==a.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${a.dtype}`);gr(t,a.shape,"TensorList shape mismatch: "),Zt(a)}),this.idTensor=Ne(0),this.maxNumElements=r,Zt(this.idTensor)}get id(){return this.idTensor.id}copy(){return new Xc([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.id))&&t.dispose()}),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(e,t,n=-1){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(n!==-1&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);gr(e,this.elementShape,"TensorList shape mismatch: ");let r=qc(this.elementShape,this.tensors,e);return L(()=>{let a=this.tensors.map(s=>H(s,r));return An(a,0)})}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let n=qc(this.elementShape,this.tensors,e),r=this.tensors.pop();return gr(r.shape,e,"TensorList shape mismatch: "),H(r,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(gr(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Zt(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${e}`);if(this.maxNumElements!==-1&&e>this.maxNumElements)throw new Error(`TensorListResize input size ${e} is greater maxNumElement ${this.maxNumElements}.`);this.tensors.length=e}getItem(e,t,n){if(n!==this.elementDtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${this.elementDtype}`);if(e<0||e>this.tensors.length)throw new Error(`Trying to access element ${e} in a list with ${this.tensors.length} elements.`);if(this.tensors[e]==null)throw new Error(`element at index ${e} is null.`);gr(this.tensors[e].shape,t,"TensorList shape mismatch: ");let r=qc(this.elementShape,this.tensors,t);return H(this.tensors[e],r)}setItem(e,t){if(t.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t.dtype}, but list elements ${this.elementDtype}`);if(e<0||this.maxNumElements!==-1&&e>=this.maxNumElements)throw new Error(`Trying to set element ${e} in a list with max ${this.maxNumElements} elements.`);gr(this.elementShape,t.shape,"TensorList shape mismatch: "),Zt(t),this.tensors[e]=t}gather(e,t,n){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);gr(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());let r=qc(this.elementShape,this.tensors,n);return e.length===0?Ir([],[0].concat(r)):L(()=>{let a=e.map(s=>H(this.tensors[s],r));return An(a,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);gr(this.elementShape,t,"TensorList shape mismatch: ");let n=qc(this.elementShape,this.tensors,t);return this.size()===0?Ir([],[0].concat(n)):L(()=>{let r=this.tensors.map(a=>H(a,n));return ot(r,0)})}};function Tre(e,t,n){let r=e.dtype;if(e.shape.length<1)throw new Error(`Tensor must be at least a vector, but saw shape: ${e.shape}`);if(e.dtype!==n)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${n}`);let a=e.shape.slice(1);gr(a,t,"TensorList shape mismatch: ");let s=pr(e);return new Xc(s,t,r)}function Ere(e,t,n){return new Xc([],e,t,n)}function Cre(e,t,n,r){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let a=Math.max(...t);if(r!=null&&r!==-1&&a>=r)throw new Error(`Max index must be < array size (${a}  vs. ${r})`);let s=new Xc([],n,e.dtype,r),i=pr(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function Rre(e,t,n){let r=0,a=t.map(c=>(r+=c,r));if(r!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to
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r=k("size",e,t,n),a=k("dtype",e,t,n),s=k("elementShape",e,t,n),i=k("dynamicSize",e,t,n),o=k("clearAfterRead",e,t,n),l=k("identicalElementShapes",e,t,n),u=k("name",e,t,n),c=new Dre(u,a,r,s,l,i,o);return n.addTensorArray(c),[c.idTensor,Ne(1)]}case"TensorArrayWriteV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.write(a,s),[i.idTensor]}case"TensorArrayReadV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,s)]}case"TensorArrayScatterV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.scatter(a,s),[i.idTensor]}case"TensorArrayConcatV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),s=k("dtype",e,t,n);return[a.concat(s)]}case"TensorArraySplitV3":{let r=k("tensorArrayId",e,t,n),a=k("tensor",e,t,n),s=k("lengths",e,t,n),i=n.getTensorArray(r.id);return i.split(s,a),[i.idTensor]}case"TensorArraySizeV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return[Ne(a.size(),"int32")]}case"TensorArrayCloseV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return a.clearAndClose(),[a.idTensor]}case"TensorListSetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorList(r.id);return i.setItem(a,s),[i.idTensor]}case"TensorListGetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).getItem(a,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let r=k("indices",e,t,n),a=k("tensor",e,t,n),s=k("elementShape",e,t,n),i=k("numElements",e,t,n),o=Pre(a,r,s,i);return n.addTensorList(o),[o.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let r=k("elementShape",e,t,n),a=k("elementDType",e,t,n),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,n),o=zre(r,a,i);return n.addTensorList(o),[o.idTensor]}case"TensorListGather":{let r=k("tensorListId",e,t,n),a=k("indices",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,i,s)]}case"TensorListStack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=k("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,s,i)]}case"TensorListFromTensor":{let r=k("tensor",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=Ore(r,a,s);return n.addTensorList(i),[i.idTensor]}case"TensorListConcat":{let r=k("tensorListId",e,t,n),a=n.getTensorList(r.id),s=k("dtype",e,t,n),i=k("elementShape",e,t,n);return[a.concat(s,i)]}case"TensorListPushBack":{let r=k("tensorListId",e,t,n),a=k("tensor",e,t,n),s=n.getTensorList(r.id);return s.pushBack(a),[s.idTensor]}case"TensorListPopBack":{let 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l=Lv(s.op);if(l&&l.customExecutor)return l.customExecutor(new Fre(s,i,o));throw TypeError(`Custom op ${s.op} is not registered.`);default:throw TypeError(`Unknown op '${s.op}'. 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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 Eg(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 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Missing the following inputs: [${r}]`)}return aae(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let r=n.map(c=>this.graph.nodes[Hn(c)[0]]),a=t.map(c=>Hn(c)[0]),s=a.map(c=>this.graph.nodes[c]);s.length===0&&(s=this._outputs);let i=this.getCompilationKey(r,s),o=this.compiledMap.get(i);o==null&&(o=this.compile(e,s),this.compiledMap.set(i,o));let l={},u={};return W(()=>{let c=new c6(this.weightMap,l,u,this.functionExecutorMap),h=Object.assign({},this.weightMap);Object.keys(e).forEach(f=>{let[m,A]=Hn(f),y=[];y[A]=e[f],h[m]=y});let d=this.getFrozenTensorIds(h),p={};for(let f=0;f<o.length;f++){let m=o[f];if(!h[m.name]){let A=u6(m,h,c,this._resourceManager);if(v.isPromise(A))throw new Error(`The execution of the op '${m.op}' returned a promise. 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u}processChildNodes(e,t,n,r,a,s){e.children.forEach(i=>{let[o]=xa(i.name,n);a[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!$n(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(l=>!!$n(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[r]=Hn(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){let s=a.attrParams.shape.value,i=s.length===n.shape.length&&n.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${a.name}'] provided in model.execute(dict) must be [${s}], but was [${n.shape}]`)}a.attrParams.dtype&&a.attrParams.dtype.value&&v.assert(n.dtype===a.attrParams.dtype.value,()=>`The dtype of dict['${a.name}'] provided in model.execute(dict) must be ${a.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=Hn(n);return this.graph.nodes[r]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${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]=Hn(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},lae=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},uae="?tfjs-format=file",cae="model.json",p6=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new lae}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=Nn.browserHTTPRequest(e,this.loadOptions);else{let t=Nn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(Nn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${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}.${t.versions.minConsumer}`;let r=Nn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new Eg(a6.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=a6.Instance.transformGraph(e.modelInitializer);this.initializer=new Eg(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=Nn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${e}'`);e=n[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}predict(e,t){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof qe)&&!Array.isArray(e))return e;if(e=Array.isArray(e)?e:[e],e.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function Ft(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. 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At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new E6(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(a),r({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),Ir(n,t)}},C6=class extends en{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=hn([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=En([s,a,o,i],[1,4])}else this.cropBox=En([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new C6(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=pl.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return W(()=>{let t=mn(xe(e,"float32"),0),n;n=Ke.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return G(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},R6=class{},F6=class extends en{split(e){return new Hae(this,e)}},Hae=class extends F6{constructor(e,t){super();this.upstream=e,this.impl=new jae(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},jae=class extends Fg{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},qae=class extends en{decodeUTF8(){return new Gae(this)}},Gae=class extends F6{constructor(e){super();this.upstream=e,this.impl=new Xae(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Xae=class extends Fg{constructor(e){super();if(this.upstream=e,J().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=Mk();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return J().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},M6=class extends qae{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(J().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let r=new FileReader;r.onload=s=>{let i=r.result;if(i instanceof 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R6{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return $6(this.url)?new y6(this.url,this.fileOptions).iterator():Zae(this.url,this.fileOptions)}};function fae(e,t={}){return new A6(new g6(e),t)}function mae(e){let t=Rg(e);return jn(async()=>t)}function Aae(e){return jn(async()=>{let t=await e();return Rg(()=>t.next())})}async function yae(e,t){return C6.create(e,t)}async function gae(e){return E6.create(e)}var xae="3.3.0",Yae={tfjs:$k,"tfjs-core":Dk,"tfjs-data":Ok,"tfjs-layers":zk,"tfjs-converter":Pk,"tfjs-backend-cpu":$w,"tfjs-backend-webgl":n_,"tfjs-backend-wasm":G3};var Gn={name:"humangl",priority:99,canvas:null,gl:null,width:1024,height:1024,webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function D6(){if(!Qf(Gn.name)){Me("backend registration:",Gn.name);try{Gn.canvas=typeof OffscreenCanvas!="undefined"?new 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rse=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],ase=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],sse=[33,133,362,263,1,78,308],Bhe=rse.map(e=>Og[e]),Vhe=ase.map(e=>Og[e]),Uhe=sse.map(e=>Og[e]);var zg=ea.leftEyeLower0,Pg=ea.rightEyeLower0,nu={leftBounds:[zg[0],zg[zg.length-1]],rightBounds:[Pg[0],Pg[Pg.length-1]]},I0={count:468,mouth:13,symmetryLine:[13,ea.midwayBetweenEyes[0]]},H6={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},ru={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function N0(e,t,n,r){for(let a=0;a<Dg.length;a++){let{key:s,indices:i}=Dg[a],o=ea[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let u=i[l];e[o[l]]=[t[u][0],t[u][1],(t[u][2]+e[o[l]][2])/2]}}}var Lg=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Kc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?k0(r,[0,0]):v0,l=r!==0?i.map(h=>[...U6(h,o),h[2]]):i,u=r!==0?V6(a):v0,c=[...eu({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+as(c,u[0]),h[1]+as(c,u[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[nu.leftBounds[0]][2],r=t[nu.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=_0(b0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Kc(i),l=Ke.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&_r.flags.IS_BROWSER&&(l=Ke.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<ru.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],u=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],u])}return{rawCoords:s,iris:s.slice(ru.index)}}getAdjustedIrisCoords(t,n,r){let a=t[ea[`${r}EyeUpper0`][ru.upperCenter]][2],s=t[ea[`${r}EyeLower0`][ru.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let u=i;return l===2?u=a:l===4&&(u=s),[o[0],o[1],u]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=L6({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=b0(o),u=_0(l),c=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...u,confidence:h,landmarks:c}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=W(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,u,c=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&_r.flags.IS_BROWSER){let[b,x]=i.landmarks.length>=I0.count?I0.symmetryLine:H6.symmetryLine;c=$g(i.landmarks[b],i.landmarks[x]);let N=eu({startPoint:i.startPoint,endPoint:i.endPoint}),S=[N[0]/t.shape[2],N[1]/t.shape[1]],T=Ke.rotateWithOffset(t,c,0,S);h=k0(-c,N),n.face.mesh.enabled?u=tu({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.meshSize,this.meshSize]).div(255):u=tu({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.boxSize,this.boxSize]).div(255)}else{h=v0;let b=t.clone();n.face.mesh.enabled?u=tu({startPoint:i.startPoint,endPoint:i.endPoint},b,[this.meshSize,this.meshSize]).div(255):u=tu({startPoint:i.startPoint,endPoint:i.endPoint},b,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:i.confidence,confidence:i.confidence,image:u};let[,d,p]=this.meshDetector.predict(u),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=G(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:b,boxSize:x,crop:N}=this.getEyeBox(A,u,nu.leftBounds[0],nu.leftBounds[1],!0),{box:S,boxSize:T,crop:M}=this.getEyeBox(A,u,nu.rightBounds[0],nu.rightBounds[1]),z=this.irisModel.predict(lt([N,M])).dataSync(),B=z.slice(0,ru.numCoordinates*3),{rawCoords:U,iris:H}=this.getEyeCoords(B,b,x,!0),X=z.slice(ru.numCoordinates*3),{rawCoords:j,iris:ee}=this.getEyeCoords(X,S,T),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(N0(A,U,"left",null),N0(A,j,"right",null)):Y<1?N0(A,U,"left",["EyeUpper0","EyeLower0"]):N0(A,j,"right",["EyeUpper0","EyeLower0"]);let se=this.getAdjustedIrisCoords(A,H,"left"),ne=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(se).concat(ne)}let y=this.transformRawCoords(A,i,c,h);i=b0(this.calculateLandmarksBoundingBox(y),1.5);let g=En(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&n.face.detector.return&&_r.flags.IS_BROWSER){let[b,x]=i.landmarks.length>=I0.count?I0.symmetryLine:H6.symmetryLine;c=$g(i.landmarks[b],i.landmarks[x]);let N=eu({startPoint:i.startPoint,endPoint:i.endPoint}),S=[N[0]/t.shape[2],N[1]/t.shape[1]],T=Ke.rotateWithOffset(t,c,0,S);h=k0(-c,N),u=tu({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.meshSize,this.meshSize]).div(255)}let w={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:u,rawCoords:A},_=_0(i);return this.storedBoxes[o]={..._,landmarks:y,confidence:i.confidence,faceConfidence:f},w}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var B2=Eh(G6());var Vg={};or(Vg,{load:()=>Ug,predict:()=>Hg});var Bg={};function xr(e,t){if(!t||!t.kernels)return;let n=5,r=t.kernels.filter(o=>o.kernelTimeMs>0).reduce((o,l)=>o+=l.kernelTimeMs,0),a=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.kernelTimeMs>0).sort((o,l)=>l.kernelTimeMs-o.kernelTimeMs),s=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.totalBytesSnapshot>0).sort((o,l)=>l.totalBytesSnapshot-o.totalBytesSnapshot);a.length>n&&(a.length=n),s.length>n&&(s.length=n);let i={newBytes:t.newBytes,newTensors:t.newTensors,peakBytes:t.peakBytes,numKernelOps:t.kernels.length,timeKernelOps:r,slowestKernelOps:a,largestKernelOps:s};Bg[e]=i,Me("Human profiler",e,i)}var ss,S0={age:0},T0=Number.MAX_SAFE_INTEGER;async function Ug(e){return ss||(ss=await Ft(e.face.age.modelPath),e.debug&&Me(`load model: ${e.face.age.modelPath.match(/\/(.*)\./)[1]}`)),ss}async function Hg(e,t){return ss?T0<t.face.age.skipFrames&&t.videoOptimized&&S0.age&&S0.age>0?(T0++,S0):(t.videoOptimized?T0=0:T0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ke.resizeBilinear(e,[ss.inputs[0].shape[2],ss.inputs[0].shape[1]],!1),a=P(r,[255]);Re(r);let s,i={age:0};if(!t.profile)t.face.age.enabled&&(s=await ss.predict(a));else{let o=t.face.age.enabled?await Jn(()=>ss.predict(a)):{};s=o.result.clone(),o.result.dispose(),xr("age",o)}if(a.dispose(),s){let o=s.dataSync();i.age=Math.trunc(10*o[0])/10}s.dispose(),S0=i,n(i)})):null}var jg={};or(jg,{load:()=>Kg,predict:()=>Zg});var ba,Gg={gender:""},E0=Number.MAX_SAFE_INTEGER,qg=!1,Xg=[.2989,.587,.114];async function Kg(e){return ba||(ba=await Ft(e.face.gender.modelPath),qg=ba.inputs[0].shape[3]===1,e.debug&&Me(`load model: ${e.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),ba}async function Zg(e,t){return ba?E0<t.face.gender.skipFrames&&t.videoOptimized&&Gg.gender!==""?(E0++,Gg):(t.videoOptimized?E0=0:E0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ke.resizeBilinear(e,[ba.inputs[0].shape[2],ba.inputs[0].shape[1]],!1),a;qg?a=W(()=>{let[o,l,u]=Ht(r,3,3),c=P(o,Xg[0]),h=P(l,Xg[1]),d=P(u,Xg[2]);return Wa([c,h,d]).sub(.5).mul(2)}):a=P(r,[255]),Re(r);let s,i={gender:"",confidence:0};if(!t.profile)t.face.gender.enabled&&(s=await ba.predict(a));else{let o=t.face.gender.enabled?await Jn(()=>ba.predict(a)):{};s=o.result.clone(),o.result.dispose(),xr("gender",o)}if(a.dispose(),s){let o=s.dataSync();if(qg)(o[0]>t.face.gender.minConfidence||o[1]>t.face.gender.minConfidence)&&(i.gender=o[0]>o[1]?"female":"male",i.confidence=o[0]>o[1]?Math.trunc(100*o[0])/100:Math.trunc(100*o[1])/100);else{let l=Math.trunc(200*Math.abs(o[0]-.5))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]<=.5?"female":"male",i.confidence=Math.min(.99,l))}}s.dispose(),Gg=i,n(i)})):null}var Yg={};or(Yg,{load:()=>e2,predict:()=>t2});var ose=["angry","disgust","fear","happy","sad","surprise","neutral"],is,Jg=[],C0=Number.MAX_SAFE_INTEGER,Qg=[.2989,.587,.114];async function 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b=this.transformRawCoords(_,p,l,d),x=this.getBoxForHandLandmarks(b);this.storedBoxes[i]=x;let N={landmarks:b,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(N)}else this.storedBoxes[i]=null;y.dispose()}else{let l=D0(O0(o),A4),u={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(u)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var g4=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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Ft(e.body.modelPath),wr.width=parseInt(wr.signature.inputs["input_1:0"].tensorShape.dim[2].size),wr.height=parseInt(wr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Me(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),wr}async function C2(e,t){if(!wr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=Ke.resizeBilinear(e,[wr.width,wr.height],!1),a=_e(r,[255]);r.dispose();let s;if(t.profile){let u=await Jn(()=>wr.predict(a));s=u.result.find(c=>c.size===195||c.size===155).dataSync(),u.result.forEach(c=>c.dispose()),xr("blazepose",u)}else{let u=await wr.predict(a);s=u.find(c=>c.size===195||c.size===155).dataSync(),u.forEach(c=>c.dispose())}a.dispose();let i=[],o=s.length===195?x4:w4,l=5;for(let u=0;u<s.length/l;u++)i.push({id:u,part:o[u],position:{x:Math.trunc(n.width*s[l*u+0]/255),y:Math.trunc(n.height*s[l*u+1]/255),z:Math.trunc(s[l*u+2])+0},score:(100-Math.trunc(100/(1+Math.exp(s[l*u+3]))))/100,presence:(100-Math.trunc(100/(1+Math.exp(s[l*u+4]))))/100});return[{keypoints:i}]}var R2={};or(R2,{load:()=>M2,predict:()=>$2});var Dr,F2=[],z0=Number.MAX_SAFE_INTEGER,P0=2.5,Rse=["person","bicycle","car","motorcycle","airplane","bus","train","vehicle","boat","traffic light","fire hydrant","stop sign","parking meter","bench","animal","animal","animal","animal","animal","animal","animal","bear","animal","animal","backpack","umbrella","handbag","tie","suitcase","frisbee","skis","snowboard","sports ball","kite","baseball bat","baseball glove","skateboard","surfboard","tennis racket","bottle","wine glass","cup","fork","knife","spoon","bowl","banana","apple","sandwich","orange","broccoli","carrot","hot dog","pizza","pastry","cake","chair","couch","potted plant","bed","dining 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e?e.map(t=>t.id===0&&t.iterationId===0?"":`${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 p6(e,t,n,r){let a=new Set,s=[],i=null,o=null,l=new Set,u=Object.keys(e).map(d=>jn(d)[0]),c=[];r!=null&&(c=r.map(d=>jn(d.name)[0]));let h=[...t];for(;h.length>0;){let d=h.pop();if((d6(d)||Xre(d)||Kre(d))&&i==null&&(i=d,o=i.children.map(p=>p.name).filter(p=>a.has(p))),a.add(d.name),n[d.name]==null&&u.indexOf(d.name)===-1&&c.indexOf(d.name)===-1){if(d.inputs.length===0){s.push(d.name);continue}d.inputs.forEach(p=>{l.has(p.name)||(l.add(p.name),h.push(p))})}}return{inputs:e,outputs:t,usedNodes:a,missingInputs:s,dynamicNode:i,syncInputs:o}}function Zre(e,t,n){let{usedNodes:r,inputs:a}=n,s=[],i=Object.keys(a).map(c=>jn(c)[0]).map(c=>e.nodes[c]),o=e.initNodes;i.forEach(c=>{r.has(c.name)&&s.push(c)}),e.weights.forEach(c=>{r.has(c.name)&&s.push(c)}),o!=null&&o.forEach(c=>{r.has(c.name)&&s.push(c)});let l=new Set,u=[];for(;s.length>0;){let c=s.pop();l.add(c.name),t[c.name]||u.push(c),c.children.forEach(h=>{!l.has(h.name)&&r.has(h.name)&&h.inputs.every(d=>l.has(d.name))&&s.push(h)})}return u}var Yre=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],Jre=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],Qre=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function d6(e){return Yre.indexOf(e.op)>=0}function Xre(e){return Jre.indexOf(e.op)>=0}function Kre(e){return Qre.indexOf(e.op)>=0}var Eg=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 Eg(e.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(r=>r.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){let n=e.map(a=>a.name).sort(),r=t.map(a=>a.name).sort();return n.join(this.SEPERATOR)+"--"+r.join(this.SEPERATOR)}compile(e,t){let n=p6(e,t,this.weightMap,this._initNodes),{missingInputs:r,dynamicNode:a,syncInputs:s}=n;if(a!=null)throw new Error(`This execution contains the node '${a.name}', which has the dynamic op '${a.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${s}]`);if(r.length>0){let i=t.map(l=>l.name),o=Object.keys(e);throw new Error(`Cannot compute the outputs [${i}] from the provided inputs [${o}]. Missing the following inputs: [${r}]`)}return Zre(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let r=n.map(c=>this.graph.nodes[jn(c)[0]]),a=t.map(c=>jn(c)[0]),s=a.map(c=>this.graph.nodes[c]);s.length===0&&(s=this._outputs);let i=this.getCompilationKey(r,s),o=this.compiledMap.get(i);o==null&&(o=this.compile(e,s),this.compiledMap.set(i,o));let l={},u={};return L(()=>{let c=new h6(this.weightMap,l,u,this.functionExecutorMap),h=Object.assign({},this.weightMap);Object.keys(e).forEach(f=>{let[m,A]=jn(f),y=[];y[A]=e[f],h[m]=y});let d=this.getFrozenTensorIds(h),p={};for(let f=0;f<o.length;f++){let m=o[f];if(!h[m.name]){let A=c6(m,h,c,this._resourceManager);if(v.isPromise(A))throw new Error(`The execution of the op '${m.op}' returned a promise. 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Fae(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new Tae(this,e,t)}columnMajorBatch(e,t=!0,n=b6){return this.rowMajorBatch(e,t).map(r=>mae(r,n))}concatenate(e,t){return new I6(k6([this,e]),t)}take(e){return e<0||e==null?this:new Sae(this,e)}skip(e){return e<0||e==null?this:new Nae(this,e)}prefetch(e){return new S6(this,e)}shuffle(e,t){return new Mae(this,e,t)}serial(){return new Iae(this)}},wae=class extends en{constructor(e){super();this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:xae(e),done:!1}}},bae=class extends en{constructor(e){super();this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},Iae=class extends en{constructor(e){super();this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},Nae=class extends en{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;Re(e.value)}return this.upstream.next()}},Sae=class extends en{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},Tae=class extends en{constructor(e,t,n=!0){super();this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},Eae=class extends en{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Re(e.value)}}},Cae=class extends en{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=vr.getTensorsInContainer(e.value),n=this.transform(e.value),r=vr.getTensorsInContainer(n);for(let a of t)vr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Rae=class extends en{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},N6=class extends en{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=vr.getTensorsInContainer(e.value),n=await this.transform(e.value),r=vr.getTensorsInContainer(n);for(let a of t)vr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Fg=class extends en{constructor(){super();this.outputQueue=new Cg,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},Fae=class extends Fg{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=vr.getTensorsInContainer(e.value),n=this.transform(e.value),r=vr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let a of t)vr.isTensorInList(a,r)||a.dispose();return!0}},I6=class extends en{constructor(e,t){super();this.baseErrorHandler=t,this.lastRead=null,this.iterator=null,this.moreIterators=e}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(e){if(await e,this.iterator==null){let n=await this.moreIterators.next();if(n.done)return{value:null,done:!0};this.iterator=n.value,this.baseErrorHandler!=null&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}let t=await this.iterator.next();return t.done?(this.iterator=null,this.readFromChain(e)):t}},rs;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(rs||(rs={}));var vae=class extends en{constructor(e,t=rs.FAIL){super();this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function r(s){return s instanceof en?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await _6(this.iterators,r);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case rs.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case rs.SHORTEST:return{value:null,done:!0};case rs.LONGEST:default:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},S6=class extends en{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new v6(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},Mae=class extends S6{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=pae.alea(n||v.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},Jl=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
+      ${e}`);let r;return this.size===Infinity||this.size==null?r=this.size:t?r=Math.ceil(this.size/e):r=Math.floor(this.size/e),Hn(async()=>(await n.iterator()).columnMajorBatch(e,t,$ae),r)}concatenate(e){let t=this,n;return this.size===Infinity||e.size===Infinity?n=Infinity:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Hn(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===Infinity?n=Infinity:n=null,Hn(async()=>(await t.iterator()).filter(r=>L(()=>e(r))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Hn(async()=>(await t.iterator()).map(n=>L(()=>e(n))),this.size)}mapAsync(e){let t=this;return Hn(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Hn(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=Infinity:n=null,Hn(async()=>{let r=Rg(async()=>({value:await t.iterator(),done:!1}));return _ae(r.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Hn(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let r=this,a=dae.alea(t||v.now().toString());return Hn(async()=>{let s=a.int32();return n&&(s+=a.int32()),(await r.iterator()).shuffle(e,s.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Hn(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Jl.MAX_BUFFER_SIZE=1e4;function Hn(e,t=null){return new class extends Jl{constructor(){super(...arguments);this.size=t}async iterator(){return e()}}}function aae(e){return Hn(async()=>k6(e),e.length)}function sae(e){if(!Ql(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Hn(async()=>{let n=await _6(e,r=>{if(r instanceof Jl)return{value:r.iterator(),recurse:!1};if(Ql(r))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return kae(n,rs.SHORTEST)},t)}function $ae(e){if(e===null)return null;let t=e[0];return yae(t)?{value:Dae(e),recurse:!1}:{value:null,recurse:!0}}function Dae(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof qe?An(e):Ir(e)}var A6=class extends Jl{constructor(e){super();this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
+`).map(e=>(e.endsWith("\r")&&(e=e.slice(0,-1)),e))}},w0='"',Kc=Symbol("out"),T6=Symbol("field"),b0=Symbol("quote"),Mg=Symbol("quoteafterquote"),E6=Symbol("quoteinquote"),y6=class extends Jl{constructor(e,t){super();this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new A6(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((r,a)=>(r[a]=r[a]+1||1,r),{}),n=Object.keys(t).filter(r=>t[r]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let r of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(r)===-1)throw new Error('The key "'+r+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},r={};for(let a=0;a<this.fullColumnNames.length;a++){let s=this.fullColumnNames[a],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[a],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let u=Number(o);if(isNaN(u))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=u;else switch(i.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(o);break;default:l=u}}i&&i.isLabel?r[s]=l:n[s]=l}}return Object.keys(r).length===0?n:{xs:n,ys:r}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],r=0,a=e.length,s=Kc;for(let i=0;i<a;i++)switch(s){case Kc:switch(e.charAt(i)){case w0:r=i+1,s=b0;break;case this.delimiter:if(r=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=Kc;break;default:s=T6,r=i;break}break;case T6:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i)),s=Kc,r=i+1;break;default:}break;case b0:switch(e.charAt(i)){case w0:s=Mg;break;default:}break;case Mg:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i-1)),s=Kc,r=i+1;break;case w0:s=b0;break;default:s=E6;break}break;case E6:switch(e.charAt(i)){case w0:s=b0;break;default:}break;default:}if(s===Mg?n.push(e.substring(r,a-1)):n.push(e.substring(r)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},C6=class extends en{constructor(e){super();this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new C6(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(a),r({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),Ir(n,t)}},R6=class extends en{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=hn([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=En([s,a,o,i],[1,4])}else this.cropBox=En([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new R6(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=pl.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: 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Kae=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],Zae=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],Yae=[33,133,362,263,1,78,308],Mhe=Kae.map(e=>Og[e]),$he=Zae.map(e=>Og[e]),Dhe=Yae.map(e=>Og[e]);var zg=ea.leftEyeLower0,Pg=ea.rightEyeLower0,nu={leftBounds:[zg[0],zg[zg.length-1]],rightBounds:[Pg[0],Pg[Pg.length-1]]},N0={count:468,mouth:13,symmetryLine:[13,ea.midwayBetweenEyes[0]]},H6={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},ru={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function S0(e,t,n,r){for(let a=0;a<Dg.length;a++){let{key:s,indices:i}=Dg[a],o=ea[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let u=i[l];e[o[l]]=[t[u][0],t[u][1],(t[u][2]+e[o[l]][2])/2]}}}var Lg=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.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,a){let s=Zc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?I0(r,[0,0]):k0,l=r!==0?i.map(h=>[...j6(h,o),h[2]]):i,u=r!==0?U6(a):k0,c=[...eu({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+as(c,u[0]),h[1]+as(c,u[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[nu.leftBounds[0]][2],r=t[nu.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=v0(_0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Zc(i),l=Ke.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&_r.flags.IS_BROWSER&&(l=Ke.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<ru.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],u=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],u])}return{rawCoords:s,iris:s.slice(ru.index)}}getAdjustedIrisCoords(t,n,r){let a=t[ea[`${r}EyeUpper0`][ru.upperCenter]][2],s=t[ea[`${r}EyeLower0`][ru.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let u=i;return l===2?u=a:l===4&&(u=s),[o[0],o[1],u]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=W6({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=_0(o),u=v0(l),c=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...u,confidence:h,landmarks:c}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=L(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,u,c=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&_r.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:H6.symmetryLine;c=$g(i.landmarks[_],i.landmarks[x]);let N=eu({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=Ke.rotateWithOffset(t,c,0,T);h=I0(-c,N),n.face.mesh.enabled?u=tu({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255):u=tu({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{h=k0;let _=t.clone();n.face.mesh.enabled?u=tu({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):u=tu({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:i.confidence,confidence:i.confidence,image:u};let[,d,p]=this.meshDetector.predict(u),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=H(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:_,boxSize:x,crop:N}=this.getEyeBox(A,u,nu.leftBounds[0],nu.leftBounds[1],!0),{box:T,boxSize:E,crop:M}=this.getEyeBox(A,u,nu.rightBounds[0],nu.rightBounds[1]),B=this.irisModel.predict(ot([N,M])).dataSync(),V=B.slice(0,ru.numCoordinates*3),{rawCoords:U,iris:j}=this.getEyeCoords(V,_,x,!0),X=B.slice(ru.numCoordinates*3),{rawCoords:G,iris:ee}=this.getEyeCoords(X,T,E),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(S0(A,U,"left",null),S0(A,G,"right",null)):Y<1?S0(A,U,"left",["EyeUpper0","EyeLower0"]):S0(A,G,"right",["EyeUpper0","EyeLower0"]);let se=this.getAdjustedIrisCoords(A,j,"left"),ne=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(se).concat(ne)}let y=this.transformRawCoords(A,i,c,h);i=_0(this.calculateLandmarksBoundingBox(y),1.5);let g=En(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&n.face.detector.return&&_r.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=N0.count?N0.symmetryLine:H6.symmetryLine;c=$g(i.landmarks[_],i.landmarks[x]);let N=eu({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],E=Ke.rotateWithOffset(t,c,0,T);h=I0(-c,N),u=tu({startPoint:i.startPoint,endPoint:i.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let w={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:u,rawCoords:A},b=v0(i);return this.storedBoxes[o]={...b,landmarks:y,confidence:i.confidence,faceConfidence:f},w}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var W2=Ch(q6());var Vg={};or(Vg,{load:()=>Ug,predict:()=>jg});var Bg={};function xr(e,t){if(!t||!t.kernels)return;let n=5,r=t.kernels.filter(o=>o.kernelTimeMs>0).reduce((o,l)=>o+=l.kernelTimeMs,0),a=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.kernelTimeMs>0).sort((o,l)=>l.kernelTimeMs-o.kernelTimeMs),s=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.totalBytesSnapshot>0).sort((o,l)=>l.totalBytesSnapshot-o.totalBytesSnapshot);a.length>n&&(a.length=n),s.length>n&&(s.length=n);let i={newBytes:t.newBytes,newTensors:t.newTensors,peakBytes:t.peakBytes,numKernelOps:t.kernels.length,timeKernelOps:r,slowestKernelOps:a,largestKernelOps:s};Bg[e]=i,Me("Human profiler",e,i)}var ss,T0={age:0},E0=Number.MAX_SAFE_INTEGER;async function Ug(e){return ss||(ss=await Ft(e.face.age.modelPath),e.debug&&Me(`load model: ${e.face.age.modelPath.match(/\/(.*)\./)[1]}`)),ss}async function jg(e,t){return ss?E0<t.face.age.skipFrames&&t.videoOptimized&&T0.age&&T0.age>0?(E0++,T0):(t.videoOptimized?E0=0:E0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ke.resizeBilinear(e,[ss.inputs[0].shape[2],ss.inputs[0].shape[1]],!1),a=O(r,[255]);Re(r);let s,i={age:0};if(!t.profile)t.face.age.enabled&&(s=await ss.predict(a));else{let o=t.face.age.enabled?await Jn(()=>ss.predict(a)):{};s=o.result.clone(),o.result.dispose(),xr("age",o)}if(a.dispose(),s){let o=s.dataSync();i.age=Math.trunc(10*o[0])/10}s.dispose(),T0=i,n(i)})):null}var Hg={};or(Hg,{load:()=>Kg,predict:()=>Zg});var ba,Gg={gender:""},C0=Number.MAX_SAFE_INTEGER,qg=!1,Xg=[.2989,.587,.114];async function Kg(e){return ba||(ba=await Ft(e.face.gender.modelPath),qg=ba.inputs[0].shape[3]===1,e.debug&&Me(`load model: ${e.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),ba}async function Zg(e,t){return ba?C0<t.face.gender.skipFrames&&t.videoOptimized&&Gg.gender!==""?(C0++,Gg):(t.videoOptimized?C0=0:C0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ke.resizeBilinear(e,[ba.inputs[0].shape[2],ba.inputs[0].shape[1]],!1),a;qg?a=L(()=>{let[o,l,u]=jt(r,3,3),c=O(o,Xg[0]),h=O(l,Xg[1]),d=O(u,Xg[2]);return Wa([c,h,d]).sub(.5).mul(2)}):a=O(r,[255]),Re(r);let s,i={gender:"",confidence:0};if(!t.profile)t.face.gender.enabled&&(s=await ba.predict(a));else{let o=t.face.gender.enabled?await Jn(()=>ba.predict(a)):{};s=o.result.clone(),o.result.dispose(),xr("gender",o)}if(a.dispose(),s){let o=s.dataSync();if(qg)(o[0]>t.face.gender.minConfidence||o[1]>t.face.gender.minConfidence)&&(i.gender=o[0]>o[1]?"female":"male",i.confidence=o[0]>o[1]?Math.trunc(100*o[0])/100:Math.trunc(100*o[1])/100);else{let l=Math.trunc(200*Math.abs(o[0]-.5))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]<=.5?"female":"male",i.confidence=Math.min(.99,l))}}s.dispose(),Gg=i,n(i)})):null}var Yg={};or(Yg,{load:()=>e2,predict:()=>t2});var Qae=["angry","disgust","fear","happy","sad","surprise","neutral"],is,Jg=[],R0=Number.MAX_SAFE_INTEGER,Qg=[.2989,.587,.114];async function e2(e){return is||(is=await Ft(e.face.emotion.modelPath),e.debug&&Me(`load model: ${e.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),is}async function t2(e,t){return is?R0<t.face.emotion.skipFrames&&t.videoOptimized&&Jg.length>0?(R0++,Jg):(t.videoOptimized?R0=0:R0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ke.resizeBilinear(e,[is.inputs[0].shape[2],is.inputs[0].shape[1]],!1),[a,s,i]=jt(r,3,3);r.dispose();let o=O(a,Qg[0]),l=O(s,Qg[1]),u=O(i,Qg[2]);a.dispose(),s.dispose(),i.dispose();let c=Wa([o,l,u]);o.dispose(),l.dispose(),u.dispose();let h=L(()=>c.sub(.5).mul(2));c.dispose();let d=[];if(t.face.emotion.enabled){let p;if(t.profile){let f=await Jn(()=>is.predict(h));p=f.result.dataSync(),f.result.dispose(),xr("emotion",f)}else{let f=await is.predict(h);p=f.dataSync(),Re(f)}for(let f=0;f<p.length;f++)p[f]>t.face.emotion.minConfidence&&d.push({score:Math.min(.99,Math.trunc(100*p[f])/100),emotion:Qae[f]});d.sort((f,m)=>m.score-f.score)}h.dispose(),Jg=d,n(d)})):null}var ta;async function n2(e){return ta||(ta=await Ft(e.face.embedding.modelPath),e.debug&&Me(`load model: ${e.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),ta}function r2(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=e.map((s,i)=>Math.abs(e[i]-t[i])**n).reduce((s,i)=>s+i,0)**(1/n);return Math.max(Math.trunc(1e3*(1-r))/1e3,0)}function X6(e,t,n=0){let r={simmilarity:0,name:"",source:"",embedding:[]};if(!e||!t||!Array.isArray(e)||!Array.isArray(t))return r;for(let a of t)if(a.embedding&&a.name){let s=r2(e,a.embedding);s>n&&s>r.simmilarity&&(r={...a,simmilarity:s})}return r}function a2(e){return L(()=>{let n=[[.05,.15,.85,.85]],r=e.image||e.tensor;if(!(r instanceof qe))return null;let a=r.shape.length===3?Ke.cropAndResize(mn(r,0),n,[0],[ta.inputs[0].shape[2],ta.inputs[0].shape[1]]):Ke.cropAndResize(r,n,[0],[ta.inputs[0].shape[2],ta.inputs[0].shape[1]]),s=[.2989,.587,.114],[i,o,l]=jt(a,3,3),u=O(i,s[0]),c=O(o,s[1]),h=O(l,s[2]),d=Wa([u,c,h]),p=An([d,d,d],3).squeeze(4),f=p.sub(p.min());return f.div(f.max())})}async function s2(e,t){return ta?new Promise(async n=>{let r=[];if(t.face.embedding.enabled){let a=a2(e);if(!t.profile)r=L(()=>[...ta.predict(a).reshape([128,2]).logSumExp(1).dataSync()]);else{let s=await Jn(()=>ta.predict({img_inputs:a}));r=[...s.result.dataSync()],s.result.dispose(),xr("emotion",s)}Re(a)}n(r)}):[]}var y2={};or(y2,{PoseNet:()=>g2,load:()=>x2});function ese(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var i2=class{constructor(t){this.model=t}predict(t){return L(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=ese(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function o2(e){return Math.floor(e/2)}var l2=class{constructor(t,n){this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=n}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(o2(t),t);)this.exchange(t,o2(t)),t=o2(t)}sink(t){for(;2*t<=this.numberOfElements;){let n=2*t;if(n<this.numberOfElements&&this.less(n,n+1)&&n++,!this.less(t,n))break;this.exchange(t,n),t=n}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,n){return this.getValueAt(t)<this.getValueAt(n)}exchange(t,n){let r=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[n],this.priorityQueue[n]=r}};function tse(e,t,n,r,a,s){let[i,o]=s.shape,l=!0,u=Math.max(n-a,0),c=Math.min(n+a+1,i);for(let h=u;h<c;++h){let d=Math.max(r-a,0),p=Math.min(r+a+1,o);for(let f=d;f<p;++f)if(s.get(h,f,e)>t){l=!1;break}if(!l)break}return l}function K6(e,t,n){let[r,a,s]=n.shape,i=new l2(r*a*s,({score:o})=>o);for(let o=0;o<r;++o)for(let l=0;l<a;++l)for(let u=0;u<s;++u){let c=n.get(o,l,u);c<e||tse(u,c,o,l,t,n)&&i.enqueue({score:c,part:{heatmapY:o,heatmapX:l,id:u}})}return i}var _a=Ch(F0());var Z6=Ch(F0());function h2(e,t,n,r){return{y:r.get(e,t,n),x:r.get(e,t,n+Z6.NUM_KEYPOINTS)}}function 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wse=5,y4=1.65,g4=[0,5,9,13,17,1,2],bse=0,_se=2,v2=class{constructor(t,n,r){this.handDetector=t,this.landmarkDetector=n,this.inputSize=r,this.storedBoxes=[],this.skipped=0,this.detectedHands=0}getBoxForPalmLandmarks(t,n){let r=t.map(s=>_2([...s,1],n)),a=this.calculateLandmarksBoundingBox(r);return O0(z0(a),wse)}getBoxForHandLandmarks(t){let n=this.calculateLandmarksBoundingBox(t),r=O0(z0(n),y4);r.palmLandmarks=[];for(let a=0;a<g4.length;a++)r.palmLandmarks.push(t[g4[a]].slice(0,2));return r}transformRawCoords(t,n,r,a){let s=D0(n),i=[s[0]/this.inputSize,s[1]/this.inputSize,(s[0]+s[1])/this.inputSize/2],o=t.map(p=>[i[0]*(p[0]-this.inputSize/2),i[1]*(p[1]-this.inputSize/2),i[2]*p[2]]),l=b2(r,[0,0]),u=o.map(p=>[..._2(p,l),p[2]]),c=A4(a),h=[...Yc(n),1],d=[os(h,c[0]),os(h,c[1])];return u.map(p=>[p[0]+d[0],p[1]+d[1],p[2]])}async estimateHands(t,n){let r=!1,a;(this.skipped===0||this.skipped>n.hand.skipFrames||!n.hand.landmarks||!n.videoOptimized)&&(a=await 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_=this.transformRawCoords(b,p,l,d),x=this.getBoxForHandLandmarks(_);this.storedBoxes[i]=x;let N={landmarks:_,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(N)}else this.storedBoxes[i]=null;y.dispose()}else{let l=O0(z0(o),y4),u={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(u)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var x4=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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w4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],b4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var wr;async function E2(e){return wr||(wr=await Ft(e.body.modelPath),wr.width=parseInt(wr.signature.inputs["input_1:0"].tensorShape.dim[2].size),wr.height=parseInt(wr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Me(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),wr}async function C2(e,t){if(!wr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=Ke.resizeBilinear(e,[wr.width,wr.height],!1),a=_e(r,[255]);r.dispose();let s;if(t.profile){let u=await Jn(()=>wr.predict(a));s=u.result.find(c=>c.size===195||c.size===155).dataSync(),u.result.forEach(c=>c.dispose()),xr("blazepose",u)}else{let u=await wr.predict(a);s=u.find(c=>c.size===195||c.size===155).dataSync(),u.forEach(c=>c.dispose())}a.dispose();let i=[],o=s.length===195?w4:b4,l=5;for(let 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a,s=[];s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),s.length===5&&W2(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftKnee"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftAnkle"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHeel"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftFoot"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),U0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightKnee"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightAnkle"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHeel"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightFoot"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),U0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftElbow"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftWrist"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftPalm"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),U0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightElbow"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightWrist"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightPalm"),a&&a.score>gt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),U0(n,s)}}}}async function j4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=le.font;for(let r of t){if(le.drawBoxes&&(n.strokeStyle=le.color,n.fillStyle=le.color,L2(n,r.box[0],r.box[1],r.box[2],r.box[3]),le.drawLabels&&(le.shadowColor&&le.shadowColor!==""&&(n.fillStyle=le.shadowColor,n.fillText("hand",r.box[0]+3,1+r.box[1]+le.lineHeight,r.box[2])),n.fillStyle=le.labelColor,n.fillText("hand",r.box[0]+2,0+r.box[1]+le.lineHeight,r.box[2])),n.stroke()),le.drawPoints&&r.landmarks&&r.landmarks.length>0)for(let a of r.landmarks)n.fillStyle=le.useDepth?`rgba(${127.5+2*a[2]}, ${127.5-2*a[2]}, 255, 0.5)`:le.color,V0(n,a[0],a[1]);if(le.drawPolygons){let a=s=>{if(!!s)for(let i=0;i<s.length;i++)n.lineWidth=le.lineWidth,n.beginPath(),n.strokeStyle=le.useDepth?`rgba(${127.5+2*s[i][2]}, ${127.5-2*s[i][2]}, 255, 0.5)`:le.color,n.moveTo(s[i>0?i-1:0][0],s[i>0?i-1:0][1]),n.lineTo(s[i][0],s[i][1]),n.stroke()};a(r.annotations.indexFinger),a(r.annotations.middleFinger),a(r.annotations.ringFinger),a(r.annotations.pinky),a(r.annotations.thumb)}}}}async function G4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=le.font;for(let r of t)if(le.drawBoxes){if(n.strokeStyle=le.color,n.fillStyle=le.color,L2(n,r.box[0],r.box[1],r.box[2]-r.box[0],r.box[3]-r.box[1]),le.drawLabels){let a=`${Math.round(100*r.score)}% ${r.label}`;le.shadowColor&&le.shadowColor!==""&&(n.fillStyle=le.shadowColor,n.fillText(a,r.box[0]+3,1+r.box[1]+le.lineHeight,r.box[2])),n.fillStyle=le.labelColor,n.fillText(a,r.box[0]+2,0+r.box[1]+le.lineHeight,r.box[2])}n.stroke()}}}async function Dse(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function Ose(e,t){!t||!e||e instanceof HTMLCanvasElement&&(U4(e,t.face),H4(e,t.body),j4(e,t.hand),V4(e,t.gesture),G4(e,t.object))}var ct=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Yc(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,r)=>(Object.keys(r||{}).forEach(a=>{let s=n[a],i=r[a];Array.isArray(s)&&Array.isArray(i)?n[a]=s.concat(...i):t(s)&&t(i)?n[a]=Yc(s,i):n[a]=i}),n),{})}var H0,je,au,Jc,Qc,Vi,Dt,j0,eh,G0,th,q0,X0,K0,V2=class{constructor(t={}){H0.set(this,void 0);je.set(this,void 0);au.set(this,void 0);Jc.set(this,void 0);Qc.set(this,void 0);Vi.set(this,void 0);Dt.set(this,(...t)=>{if(!ge(this,Jc))return;let n=this.tf.engine().state.numTensors,r=ge(this,au);oa(this,au,n);let a=n-r;a!==0&&Me(...t,a)});j0.set(this,t=>{if(!ge(this,Qc))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof qe))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});eh.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=ct();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.config.debug&&Me("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Me("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Me(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Me("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&D6();try{await this.tf.setBackend(this.config.backend)}catch(r){Me("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(Me("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Me(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),ge(this,je).backend=Math.trunc(ct()-n)}});G0.set(this,t=>{if(!t||t.length<300)return{roll:null,yaw:null,pitch:null};let n=(s,i,o,l)=>Math.atan2(l-i,o-s),r=s=>Math.abs(s*180/Math.PI%360);return{roll:n(t[33][0],t[33][1],t[263][0],t[263][1]),yaw:n(t[33][0],t[33][2],t[263][0],t[263][2]),pitch:n(t[10][1],t[10][2],t[152][1],t[152][2])}});th.set(this,async t=>{var u,c,h,d,p,f,m;let n,r,a,s,i,o=[];this.state="run:face",n=ct();let l=await((u=this.models.face)==null?void 0:u.estimateFaces(t,this.config));if(ge(this,je).face=Math.trunc(ct()-n),!l)return[];for(let A of l){if(ge(this,Dt).call(this,"Get Face"),!A.image||A.image.isDisposedInternal){Me("Face object is disposed:",A.image);continue}let y=ge(this,G0).call(this,A.mesh);ge(this,Dt).call(this,"Start Age:"),this.config.async?r=this.config.face.age.enabled?Hg(A.image,this.config):{}:(this.state="run:age",n=ct(),r=this.config.face.age.enabled?await Hg(A.image,this.config):{},ge(this,je).age=Math.trunc(ct()-n)),ge(this,Dt).call(this,"Start Gender:"),this.config.async?a=this.config.face.gender.enabled?Zg(A.image,this.config):{}:(this.state="run:gender",n=ct(),a=this.config.face.gender.enabled?await Zg(A.image,this.config):{},ge(this,je).gender=Math.trunc(ct()-n)),ge(this,Dt).call(this,"Start Emotion:"),this.config.async?s=this.config.face.emotion.enabled?t2(A.image,this.config):{}:(this.state="run:emotion",n=ct(),s=this.config.face.emotion.enabled?await t2(A.image,this.config):{},ge(this,je).emotion=Math.trunc(ct()-n)),ge(this,Dt).call(this,"End Emotion:"),ge(this,Dt).call(this,"Start Embedding:"),this.config.async?i=this.config.face.embedding.enabled?s2(A,this.config):[]:(this.state="run:embedding",n=ct(),i=this.config.face.embedding.enabled?await s2(A,this.config):[],ge(this,je).embedding=Math.trunc(ct()-n)),ge(this,Dt).call(this,"End Emotion:"),this.config.async&&([r,a,s,i]=await Promise.all([r,a,s,i])),ge(this,Dt).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((c=A==null?void 0:A.annotations)==null?void 0:c.leftEyeIris)&&((h=A==null?void 0:A.annotations)==null?void 0:h.rightEyeIris)&&(delete A.annotations.leftEyeIris,delete A.annotations.rightEyeIris);let g=((d=A.annotations)==null?void 0:d.leftEyeIris)&&((p=A.annotations)==null?void 0:p.rightEyeIris)?11.7*Math.max(Math.abs(A.annotations.leftEyeIris[3][0]-A.annotations.leftEyeIris[1][0]),Math.abs(A.annotations.rightEyeIris[4][1]-A.annotations.rightEyeIris[2][1])):0;o.push({...A,age:r.age,gender:a.gender,genderConfidence:a.confidence,emotion:s,embedding:i,iris:g!==0?Math.trunc(g)/100:0,angle:y,tensor:this.config.face.detector.return?(f=A.image)==null?void 0:f.squeeze():null}),(m=A.image)==null||m.dispose(),ge(this,Dt).call(this,"End Face")}return ge(this,Dt).call(this,"End FaceMesh:"),this.config.async&&(ge(this,je).face&&delete ge(this,je).face,ge(this,je).age&&delete ge(this,je).age,ge(this,je).gender&&delete ge(this,je).gender,ge(this,je).emotion&&delete ge(this,je).emotion),o});q0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(W0);break;case"full":n=await t(B0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});X0.set(this,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,"+B0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));K0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(W0):t(B0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=Ch,this.draw=P2,oa(this,H0,O2),this.version=z2,this.config=Yc(gt,t),this.state="idle",oa(this,au,0),oa(this,Jc,!1),oa(this,Qc,!1),oa(this,Vi,!0),oa(this,je,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=n=>D2(n,this.config),this.classes={facemesh:B2,age:Vg,gender:jg,emotion:Yg,body:this.config.body.modelPath.includes("posenet")?y2:T2,hand:k2,nanodet:R2},this.sysinfo=r5()}profileData(){return this.config.profile?Bg:{}}simmilarity(t,n){return this.config.face.embedding.enabled?r2(t,n):0}enhance(t){return a2(t)}match(t,n,r=0){return q6(t,n,r)}async load(t={}){this.state="load";let n=ct();t&&(this.config=Yc(this.config,t)),ge(this,Vi)&&(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 ge(this,eh).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.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?B2.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?Ug(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?Kg(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?e2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?n2(this.config):null),this.models.handpose||(this.config.hand.enabled?S2(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?x2(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?E2(this.config):null),this.models.nanodet||(this.config.object.enabled?M2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await B2.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await Ug(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await Kg(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await e2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await n2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await S2(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await x2(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await E2(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await M2(this.config))),ge(this,Vi)&&(this.config.debug&&Me("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),oa(this,Vi,!1));let r=Math.trunc(ct()-n);r>(ge(this,je).load||0)&&(ge(this,je).load=r)}async detect(t,n={}){return new Promise(async r=>{var p,f,m,A;this.state="config";let a;this.config=Yc(this.config,n),this.state="check";let s=ge(this,j0).call(this,t);s&&(Me(s,t),r({error:s}));let i=ct();await ge(this,eh).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),ge(this,Dt).call(this,"Start Scope:"),a=ct();let o=D2(t,this.config);if(!o||!o.tensor){Me("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}ge(this,je).image=Math.trunc(ct()-a),ge(this,Dt).call(this,"Get Image:");let l,u,c,h;this.config.async?(c=this.config.face.enabled?ge(this,th).call(this,o.tensor):[],ge(this,je).face&&delete ge(this,je).face):(this.state="run:face",a=ct(),c=this.config.face.enabled?await ge(this,th).call(this,o.tensor):[],ge(this,je).face=Math.trunc(ct()-a)),ge(this,Dt).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(p=this.models.posenet)==null?void 0:p.estimatePoses(o.tensor,this.config):[]:l=this.config.body.enabled?C2(o.tensor,this.config):[],ge(this,je).body&&delete ge(this,je).body):(this.state="run:body",a=ct(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((f=this.models.posenet)==null?void 0:f.estimatePoses(o.tensor,this.config)):[]:l=this.config.body.enabled?await C2(o.tensor,this.config):[],ge(this,je).body=Math.trunc(ct()-a)),ge(this,Dt).call(this,"End Body:"),ge(this,Dt).call(this,"Start Hand:"),this.config.async?(u=this.config.hand.enabled?(m=this.models.handpose)==null?void 0:m.estimateHands(o.tensor,this.config):[],ge(this,je).hand&&delete ge(this,je).hand):(this.state="run:hand",a=ct(),u=this.config.hand.enabled?await((A=this.models.handpose)==null?void 0:A.estimateHands(o.tensor,this.config)):[],ge(this,je).hand=Math.trunc(ct()-a)),ge(this,Dt).call(this,"End Hand:"),ge(this,Dt).call(this,"Start Object:"),this.config.async?(h=this.config.object.enabled?$2(o.tensor,this.config):[],ge(this,je).object&&delete ge(this,je).object):(this.state="run:object",a=ct(),h=this.config.object.enabled?await $2(o.tensor,this.config):[],ge(this,je).object=Math.trunc(ct()-a)),ge(this,Dt).call(this,"End Object:"),this.config.async&&([c,l,u,h]=await Promise.all([c,l,u,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),ge(this,Dt).call(this,"End Scope:");let d=[];this.config.gesture.enabled&&(a=ct(),d=[..._4(c),...b4(l),...k4(u),...v4(c)],this.config.async?ge(this,je).gesture&&delete ge(this,je).gesture:ge(this,je).gesture=Math.trunc(ct()-a)),ge(this,je).total=Math.trunc(ct()-i),this.state="idle",r({face:c,body:l,hand:u,gesture:d,object:h,performance:ge(this,je),canvas:o.canvas})})}async warmup(t={}){let n=ct();t&&(this.config=Yc(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await ge(this,q0).call(this):typeof Image!="undefined"?a=await ge(this,X0).call(this):a=await ge(this,K0).call(this),this.config.videoOptimized=r;let s=ct();return this.config.debug&&Me("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};H0=new WeakMap,je=new WeakMap,au=new WeakMap,Jc=new WeakMap,Qc=new WeakMap,Vi=new WeakMap,Dt=new WeakMap,j0=new WeakMap,eh=new WeakMap,G0=new WeakMap,th=new WeakMap,q0=new WeakMap,X0=new WeakMap,K0=new WeakMap;var nh=0,q4=!1,kt={background:"darkslategray",hover:"lightgray",itemBackground:"black",itemColor:"white",buttonBackground:"lightblue",buttonHover:"lightgreen",checkboxOn:"lightgreen",checkboxOff:"lightcoral",rangeBackground:"lightblue",rangeLabel:"white",chartColor:"lightblue"};function zse(){if(q4)return;let e=`
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P2={};or(P2,{all:()=>Tse,body:()=>H4,canvas:()=>Sse,drawOptions:()=>oe,face:()=>j4,gesture:()=>U4,hand:()=>G4,object:()=>q4});var oe={color:"rgba(173, 216, 230, 0.3)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",font:'small-caps 16px "Segoe UI"',lineHeight:20,lineWidth:6,pointSize:2,roundRect:28,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawPolygons:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,bufferedOutput:!1,useRawBoxes:!1};function U0(e,t,n,r=null){e.fillStyle=oe.useDepth&&r?`rgba(${127.5+2*(r||0)}, ${127.5-2*(r||0)}, 255, 0.3)`:oe.color,e.beginPath(),e.arc(t,n,oe.pointSize,0,2*Math.PI),e.fill()}function au(e,t,n,r,a){if(e.beginPath(),oe.useCurves){let s=(t+t+r)/2,i=(n+n+a)/2;e.ellipse(s,i,r/2,a/2,0,0,2*Math.PI)}else e.lineWidth=oe.lineWidth,e.moveTo(t+oe.roundRect,n),e.lineTo(t+r-oe.roundRect,n),e.quadraticCurveTo(t+r,n,t+r,n+oe.roundRect),e.lineTo(t+r,n+a-oe.roundRect),e.quadraticCurveTo(t+r,n+a,t+r-oe.roundRect,n+a),e.lineTo(t+oe.roundRect,n+a),e.quadraticCurveTo(t,n+a,t,n+a-oe.roundRect),e.lineTo(t,n+oe.roundRect),e.quadraticCurveTo(t,n,t+oe.roundRect,n),e.closePath();e.stroke()}function L2(e,t=[]){if(!(t===void 0||t.length===0)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=oe.useDepth&&n[2]?`rgba(${127.5+2*n[2]}, ${127.5-2*n[2]}, 255, 0.3)`:oe.color,e.fillStyle=oe.useDepth&&n[2]?`rgba(${127.5+2*n[2]}, ${127.5-2*n[2]}, 255, 0.3)`:oe.color,e.lineTo(n[0],parseInt(n[1]));e.stroke(),oe.fillPolygons&&(e.closePath(),e.fill())}}function j0(e,t=[]){if(!(t===void 0||t.length===0)){if(!oe.useCurves||t.length<=2){L2(e,t);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,a=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,a)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),oe.fillPolygons&&(e.closePath(),e.fill())}}async function U4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!n)return;n.font=oe.font,n.fillStyle=oe.color;let r=1;for(let a=0;a<t.length;a++){let s=[],i=[];if([s,i]=Object.entries(t[a]),i.length>1&&i[1].length>0){let o=s[1]>0?`#${s[1]}`:"",l=`${s[0]} ${o}: ${i[1]}`;oe.shadowColor&&oe.shadowColor!==""&&(n.fillStyle=oe.shadowColor,n.fillText(l,8,2+r*oe.lineHeight)),n.fillStyle=oe.labelColor,n.fillText(l,6,0+r*oe.lineHeight),r+=1}}}async function j4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n)for(let r of t){n.font=oe.font,n.strokeStyle=oe.color,n.fillStyle=oe.color,oe.drawBoxes&&(oe.useRawBoxes?au(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):au(n,r.box[0],r.box[1],r.box[2],r.box[3]));let a=[];if(a.push(`face confidence: ${Math.trunc(100*r.confidence)}%`),r.genderConfidence&&a.push(`${r.gender||""} ${Math.trunc(100*r.genderConfidence)}% confident`),r.age&&a.push(`age: ${r.age||""}`),r.iris&&a.push(`iris distance: ${r.iris}`),r.emotion&&r.emotion.length>0){let s=r.emotion.map(i=>`${Math.trunc(100*i.score)}% ${i.emotion}`);a.push(s.join(" "))}r.angle&&r.angle.roll&&a.push(`roll: ${Math.trunc(100*r.angle.roll)/100} yaw:${Math.trunc(100*r.angle.yaw)/100} pitch:${Math.trunc(100*r.angle.pitch)/100}`),a.length===0&&a.push("face"),n.fillStyle=oe.color;for(let s=a.length-1;s>=0;s--){let i=Math.max(r.box[0],0),o=s*oe.lineHeight+r.box[1];oe.shadowColor&&oe.shadowColor!==""&&(n.fillStyle=oe.shadowColor,n.fillText(a[s],i+5,o+16)),n.fillStyle=oe.labelColor,n.fillText(a[s],i+4,o+15)}if(n.lineWidth=1,r.mesh&&r.mesh.length>0){if(oe.drawPoints)for(let s of r.mesh)U0(n,s[0],s[1],s[2]);if(oe.drawPolygons){n.lineWidth=1;for(let s=0;s<Wi.length/3;s++){let i=[Wi[s*3+0],Wi[s*3+1],Wi[s*3+2]].map(o=>r.mesh[o]);L2(n,i)}if(r.annotations&&r.annotations.leftEyeIris){n.strokeStyle=oe.useDepth?"rgba(255, 200, 255, 0.3)":oe.color,n.beginPath();let s=Math.abs(r.annotations.leftEyeIris[3][0]-r.annotations.leftEyeIris[1][0])/2,i=Math.abs(r.annotations.leftEyeIris[4][1]-r.annotations.leftEyeIris[2][1])/2;n.ellipse(r.annotations.leftEyeIris[0][0],r.annotations.leftEyeIris[0][1],s,i,0,0,2*Math.PI),n.stroke(),oe.fillPolygons&&(n.fillStyle=oe.useDepth?"rgba(255, 255, 200, 0.3)":oe.color,n.fill())}if(r.annotations&&r.annotations.rightEyeIris){n.strokeStyle=oe.useDepth?"rgba(255, 200, 255, 0.3)":oe.color,n.beginPath();let s=Math.abs(r.annotations.rightEyeIris[3][0]-r.annotations.rightEyeIris[1][0])/2,i=Math.abs(r.annotations.rightEyeIris[4][1]-r.annotations.rightEyeIris[2][1])/2;n.ellipse(r.annotations.rightEyeIris[0][0],r.annotations.rightEyeIris[0][1],s,i,0,0,2*Math.PI),n.stroke(),oe.fillPolygons&&(n.fillStyle=oe.useDepth?"rgba(255, 255, 200, 0.3)":oe.color,n.fill())}}}}}var ls=[];async function H4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round";for(let r=0;r<t.length;r++){if(!ls[r]&&oe.bufferedOutput&&(ls[r]={...t[r]}),n.strokeStyle=oe.color,n.lineWidth=oe.lineWidth,oe.drawPoints)for(let a=0;a<t[r].keypoints.length;a++)n.fillStyle=oe.useDepth&&t[r].keypoints[a].position.z?`rgba(${127.5+2*t[r].keypoints[a].position.z}, ${127.5-2*t[r].keypoints[a].position.z}, 255, 0.5)`:oe.color,oe.bufferedOutput?(ls[r].keypoints[a][0]=(ls[r].keypoints[a][0]+t[r].keypoints[a].position.x)/2,ls[r].keypoints[a][1]=(ls[r].keypoints[a][1]+t[r].keypoints[a].position.y)/2,U0(n,ls[r].keypoints[a][0],ls[r].keypoints[a][1])):U0(n,t[r].keypoints[a].position.x,t[r].keypoints[a].position.y);if(oe.drawLabels){n.font=oe.font;for(let a of t[r].keypoints)n.fillStyle=oe.useDepth&&a.position.z?`rgba(${127.5+2*a.position.z}, ${127.5-2*a.position.z}, 255, 0.5)`:oe.color,n.fillText(`${a.part}`,a.position.x+4,a.position.y+4)}if(oe.drawPolygons){let a,s=[];s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),s.length===5&&L2(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftKnee"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftAnkle"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHeel"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftFoot"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),j0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightKnee"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightAnkle"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHeel"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightFoot"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),j0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftElbow"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftWrist"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftPalm"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),j0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightElbow"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightWrist"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightPalm"),a&&a.score>yt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),j0(n,s)}}}}async function G4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=oe.font;for(let r of t){if(oe.drawBoxes&&(n.strokeStyle=oe.color,n.fillStyle=oe.color,oe.useRawBoxes?au(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):au(n,r.box[0],r.box[1],r.box[2],r.box[3]),oe.drawLabels&&(oe.shadowColor&&oe.shadowColor!==""&&(n.fillStyle=oe.shadowColor,n.fillText("hand",r.box[0]+3,1+r.box[1]+oe.lineHeight,r.box[2])),n.fillStyle=oe.labelColor,n.fillText("hand",r.box[0]+2,0+r.box[1]+oe.lineHeight,r.box[2])),n.stroke()),oe.drawPoints&&r.landmarks&&r.landmarks.length>0)for(let a of r.landmarks)n.fillStyle=oe.useDepth?`rgba(${127.5+2*a[2]}, ${127.5-2*a[2]}, 255, 0.5)`:oe.color,U0(n,a[0],a[1]);if(oe.drawPolygons){let a=s=>{if(!!s)for(let i=0;i<s.length;i++)n.lineWidth=oe.lineWidth,n.beginPath(),n.strokeStyle=oe.useDepth?`rgba(${127.5+2*s[i][2]}, ${127.5-2*s[i][2]}, 255, 0.5)`:oe.color,n.moveTo(s[i>0?i-1:0][0],s[i>0?i-1:0][1]),n.lineTo(s[i][0],s[i][1]),n.stroke()};a(r.annotations.indexFinger),a(r.annotations.middleFinger),a(r.annotations.ringFinger),a(r.annotations.pinky),a(r.annotations.thumb)}}}}async function q4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=oe.font;for(let r of t)if(oe.drawBoxes){if(n.strokeStyle=oe.color,n.fillStyle=oe.color,oe.useRawBoxes?au(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):au(n,r.box[0],r.box[1],r.box[2],r.box[3]),oe.drawLabels){let a=`${Math.round(100*r.score)}% ${r.label}`;oe.shadowColor&&oe.shadowColor!==""&&(n.fillStyle=oe.shadowColor,n.fillText(a,r.box[0]+3,1+r.box[1]+oe.lineHeight,r.box[2])),n.fillStyle=oe.labelColor,n.fillText(a,r.box[0]+2,0+r.box[1]+oe.lineHeight,r.box[2])}n.stroke()}}}async function Sse(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function Tse(e,t){!t||!e||e instanceof HTMLCanvasElement&&(j4(e,t.face),H4(e,t.body),G4(e,t.hand),U4(e,t.gesture),q4(e,t.object))}var ut=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Jc(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,r)=>(Object.keys(r||{}).forEach(a=>{let s=n[a],i=r[a];Array.isArray(s)&&Array.isArray(i)?n[a]=s.concat(...i):t(s)&&t(i)?n[a]=Jc(s,i):n[a]=i}),n),{})}var H0,He,su,Qc,eh,Vi,Dt,G0,th,q0,nh,X0,K0,Z0,B2=class{constructor(t={}){H0.set(this,void 0);He.set(this,void 0);su.set(this,void 0);Qc.set(this,void 0);eh.set(this,void 0);Vi.set(this,void 0);Dt.set(this,(...t)=>{if(!ge(this,Qc))return;let n=this.tf.engine().state.numTensors,r=ge(this,su);oa(this,su,n);let a=n-r;a!==0&&Me(...t,a)});G0.set(this,t=>{if(!ge(this,eh))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof qe))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});th.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=ut();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.config.debug&&Me("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Me("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Me(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Me("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&O6();try{await this.tf.setBackend(this.config.backend)}catch(r){Me("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(Me("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Me(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),ge(this,He).backend=Math.trunc(ut()-n)}});q0.set(this,t=>{if(!t||t.length<300)return{roll:null,yaw:null,pitch:null};let n=(s,i,o,l)=>Math.atan2(l-i,o-s),r=s=>Math.abs(s*180/Math.PI%360);return{roll:n(t[33][0],t[33][1],t[263][0],t[263][1]),yaw:n(t[33][0],t[33][2],t[263][0],t[263][2]),pitch:n(t[10][1],t[10][2],t[152][1],t[152][2])}});nh.set(this,async t=>{var u,c,h,d,p,f,m;let n,r,a,s,i,o=[];this.state="run:face",n=ut();let l=await((u=this.models.face)==null?void 0:u.estimateFaces(t,this.config));if(ge(this,He).face=Math.trunc(ut()-n),!l)return[];for(let A of l){if(ge(this,Dt).call(this,"Get Face"),!A.image||A.image.isDisposedInternal){Me("Face object is disposed:",A.image);continue}let y=ge(this,q0).call(this,A.mesh);ge(this,Dt).call(this,"Start Age:"),this.config.async?r=this.config.face.age.enabled?jg(A.image,this.config):{}:(this.state="run:age",n=ut(),r=this.config.face.age.enabled?await jg(A.image,this.config):{},ge(this,He).age=Math.trunc(ut()-n)),ge(this,Dt).call(this,"Start Gender:"),this.config.async?a=this.config.face.gender.enabled?Zg(A.image,this.config):{}:(this.state="run:gender",n=ut(),a=this.config.face.gender.enabled?await Zg(A.image,this.config):{},ge(this,He).gender=Math.trunc(ut()-n)),ge(this,Dt).call(this,"Start Emotion:"),this.config.async?s=this.config.face.emotion.enabled?t2(A.image,this.config):{}:(this.state="run:emotion",n=ut(),s=this.config.face.emotion.enabled?await t2(A.image,this.config):{},ge(this,He).emotion=Math.trunc(ut()-n)),ge(this,Dt).call(this,"End Emotion:"),ge(this,Dt).call(this,"Start Embedding:"),this.config.async?i=this.config.face.embedding.enabled?s2(A,this.config):[]:(this.state="run:embedding",n=ut(),i=this.config.face.embedding.enabled?await s2(A,this.config):[],ge(this,He).embedding=Math.trunc(ut()-n)),ge(this,Dt).call(this,"End Emotion:"),this.config.async&&([r,a,s,i]=await Promise.all([r,a,s,i])),ge(this,Dt).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((c=A==null?void 0:A.annotations)==null?void 0:c.leftEyeIris)&&((h=A==null?void 0:A.annotations)==null?void 0:h.rightEyeIris)&&(delete A.annotations.leftEyeIris,delete A.annotations.rightEyeIris);let g=((d=A.annotations)==null?void 0:d.leftEyeIris)&&((p=A.annotations)==null?void 0:p.rightEyeIris)?11.7*Math.max(Math.abs(A.annotations.leftEyeIris[3][0]-A.annotations.leftEyeIris[1][0]),Math.abs(A.annotations.rightEyeIris[4][1]-A.annotations.rightEyeIris[2][1])):0;o.push({...A,age:r.age,gender:a.gender,genderConfidence:a.confidence,emotion:s,embedding:i,iris:g!==0?Math.trunc(g)/100:0,angle:y,tensor:this.config.face.detector.return?(f=A.image)==null?void 0:f.squeeze():null}),(m=A.image)==null||m.dispose(),ge(this,Dt).call(this,"End Face")}return ge(this,Dt).call(this,"End FaceMesh:"),this.config.async&&(ge(this,He).face&&delete ge(this,He).face,ge(this,He).age&&delete ge(this,He).age,ge(this,He).gender&&delete ge(this,He).gender,ge(this,He).emotion&&delete ge(this,He).emotion),o});X0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(B0);break;case"full":n=await t(V0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});K0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+B0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+V0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));Z0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(B0):t(V0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=Rh,this.draw=P2,oa(this,H0,O2),this.version=z2,this.config=Jc(yt,t),this.state="idle",oa(this,su,0),oa(this,Qc,!1),oa(this,eh,!1),oa(this,Vi,!0),oa(this,He,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=n=>D2(n,this.config),this.classes={facemesh:W2,age:Vg,gender:Hg,emotion:Yg,body:this.config.body.modelPath.includes("posenet")?y2:T2,hand:k2,nanodet:R2},this.sysinfo=n5()}profileData(){return this.config.profile?Bg:{}}simmilarity(t,n){return this.config.face.embedding.enabled?r2(t,n):0}enhance(t){return a2(t)}match(t,n,r=0){return X6(t,n,r)}async load(t={}){this.state="load";let n=ut();t&&(this.config=Jc(this.config,t)),ge(this,Vi)&&(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 ge(this,th).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.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?W2.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?Ug(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?Kg(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?e2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?n2(this.config):null),this.models.handpose||(this.config.hand.enabled?S2(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?x2(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?E2(this.config):null),this.models.nanodet||(this.config.object.enabled?M2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await W2.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await Ug(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await Kg(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await e2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await n2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await S2(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await x2(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await E2(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await M2(this.config))),ge(this,Vi)&&(this.config.debug&&Me("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),oa(this,Vi,!1));let r=Math.trunc(ut()-n);r>(ge(this,He).load||0)&&(ge(this,He).load=r)}async detect(t,n={}){return new Promise(async r=>{var f,m,A,y;this.state="config";let a;this.config=Jc(this.config,n),this.state="check";let s=ge(this,G0).call(this,t);s&&(Me(s,t),r({error:s}));let i=ut();await ge(this,th).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),ge(this,Dt).call(this,"Start Scope:"),a=ut();let o=D2(t,this.config);if(!o||!o.tensor){Me("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}ge(this,He).image=Math.trunc(ut()-a),ge(this,Dt).call(this,"Get Image:");let l,u,c,h;this.config.async?(c=this.config.face.enabled?ge(this,nh).call(this,o.tensor):[],ge(this,He).face&&delete ge(this,He).face):(this.state="run:face",a=ut(),c=this.config.face.enabled?await ge(this,nh).call(this,o.tensor):[],ge(this,He).face=Math.trunc(ut()-a)),ge(this,Dt).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(f=this.models.posenet)==null?void 0:f.estimatePoses(o.tensor,this.config):[]:l=this.config.body.enabled?C2(o.tensor,this.config):[],ge(this,He).body&&delete ge(this,He).body):(this.state="run:body",a=ut(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((m=this.models.posenet)==null?void 0:m.estimatePoses(o.tensor,this.config)):[]:l=this.config.body.enabled?await C2(o.tensor,this.config):[],ge(this,He).body=Math.trunc(ut()-a)),ge(this,Dt).call(this,"End Body:"),ge(this,Dt).call(this,"Start Hand:"),this.config.async?(u=this.config.hand.enabled?(A=this.models.handpose)==null?void 0:A.estimateHands(o.tensor,this.config):[],ge(this,He).hand&&delete ge(this,He).hand):(this.state="run:hand",a=ut(),u=this.config.hand.enabled?await((y=this.models.handpose)==null?void 0:y.estimateHands(o.tensor,this.config)):[],ge(this,He).hand=Math.trunc(ut()-a)),ge(this,Dt).call(this,"End Hand:"),ge(this,Dt).call(this,"Start Object:"),this.config.async?(h=this.config.object.enabled?$2(o.tensor,this.config):[],ge(this,He).object&&delete ge(this,He).object):(this.state="run:object",a=ut(),h=this.config.object.enabled?await $2(o.tensor,this.config):[],ge(this,He).object=Math.trunc(ut()-a)),ge(this,Dt).call(this,"End Object:"),this.config.async&&([c,l,u,h]=await Promise.all([c,l,u,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),ge(this,Dt).call(this,"End Scope:");let d=[];this.config.gesture.enabled&&(a=ut(),d=[...v4(c),..._4(l),...I4(u),...k4(c)],this.config.async?ge(this,He).gesture&&delete ge(this,He).gesture:ge(this,He).gesture=Math.trunc(ut()-a)),ge(this,He).total=Math.trunc(ut()-i),this.state="idle";let p={face:c,body:l,hand:u,gesture:d,object:h,performance:ge(this,He),canvas:o.canvas};r(p)})}async warmup(t={}){let n=ut();t&&(this.config=Jc(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await ge(this,X0).call(this):typeof Image!="undefined"?a=await ge(this,K0).call(this):a=await ge(this,Z0).call(this),this.config.videoOptimized=r;let s=ut();return this.config.debug&&Me("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};H0=new WeakMap,He=new WeakMap,su=new WeakMap,Qc=new WeakMap,eh=new WeakMap,Vi=new WeakMap,Dt=new WeakMap,G0=new WeakMap,th=new WeakMap,q0=new WeakMap,nh=new WeakMap,X0=new WeakMap,K0=new WeakMap,Z0=new WeakMap;var rh=0,X4=!1,vt={background:"darkslategray",hover:"lightgray",itemBackground:"black",itemColor:"white",buttonBackground:"lightblue",buttonHover:"lightgreen",checkboxOn:"lightgreen",checkboxOff:"lightcoral",rangeBackground:"lightblue",rangeLabel:"white",chartColor:"lightblue"};function Ese(){if(X4)return;let e=`
   :root { --rounded: 0.1rem; }
   .menu { position: absolute; top: 0rem; right: 0; width: max-content; padding: 0 0.2rem 0 0.2rem; line-height: 1.8rem; z-index: 10;
-          box-shadow: 0 0 8px dimgrey; background: ${kt.background}; border-radius: var(--rounded); border-color: black; border-style: solid; border-width: thin; }
+          box-shadow: 0 0 8px dimgrey; background: ${vt.background}; border-radius: var(--rounded); border-color: black; border-style: solid; border-width: thin; }
 
-  .menu:hover { box-shadow: 0 0 8px ${kt.hover}; }
+  .menu:hover { box-shadow: 0 0 8px ${vt.hover}; }
   .menu-container { display: block; max-height: 100vh; }
   .menu-container-fadeout { max-height: 0; overflow: hidden; transition: max-height, 0.5s ease; }
   .menu-container-fadein { max-height: 100vh; overflow: hidden; transition: max-height, 0.5s ease; }
@@ -4905,41 +4905,41 @@ lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
 
   .menu-list { margin-right: 0.8rem; }
   select:focus { outline: none; }
-  .menu-list-item { background: ${kt.itemBackground}; color: ${kt.itemColor}; border: none; padding: 0.2rem; font-family: inherit;
+  .menu-list-item { background: ${vt.itemBackground}; color: ${vt.itemColor}; border: none; padding: 0.2rem; font-family: inherit;
     font-variant: inherit; border-radius: var(--rounded); font-weight: 800; }
 
   .menu-chart-title { padding: 0; font-size: 0.8rem; font-weight: 800; align-items: center}
   .menu-chart-canvas { background: transparent; margin: 0.2rem 0 0.2rem 0.6rem; }
   
-  .menu-button { border: 0; background: ${kt.buttonBackground}; width: -webkit-fill-available; padding: 8px; margin: 8px; cursor: pointer; box-shadow: 4px 4px 4px 0 dimgrey;
+  .menu-button { border: 0; background: ${vt.buttonBackground}; width: -webkit-fill-available; padding: 8px; margin: 8px; cursor: pointer; box-shadow: 4px 4px 4px 0 dimgrey;
     border-radius: var(--rounded); justify-content: center; font-family: inherit; font-variant: inherit; font-size: 1rem; font-weight: 800; }
-  .menu-button:hover { background: ${kt.buttonHover}; box-shadow: 4px 4px 4px 0 black; }
+  .menu-button:hover { background: ${vt.buttonHover}; box-shadow: 4px 4px 4px 0 black; }
   .menu-button:focus { outline: none; }
 
-  .menu-checkbox { width: 2.8rem; height: 1rem; background: ${kt.itemBackground}; margin: 0.5rem 0.5rem 0 0; position: relative; border-radius: var(--rounded); }
-  .menu-checkbox:after { content: 'OFF'; color: ${kt.checkboxOff}; position: absolute; right: 0.2rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
-  .menu-checkbox:before { content: 'ON'; color: ${kt.checkboxOn}; position: absolute; left: 0.3rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
-  .menu-checkbox-label { width: 1.3rem; height: 0.8rem; cursor: pointer; position: absolute; top: 0.1rem; left: 0.1rem; z-index: 1; background: ${kt.checkboxOff};
+  .menu-checkbox { width: 2.8rem; height: 1rem; background: ${vt.itemBackground}; margin: 0.5rem 0.5rem 0 0; position: relative; border-radius: var(--rounded); }
+  .menu-checkbox:after { content: 'OFF'; color: ${vt.checkboxOff}; position: absolute; right: 0.2rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
+  .menu-checkbox:before { content: 'ON'; color: ${vt.checkboxOn}; position: absolute; left: 0.3rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }
+  .menu-checkbox-label { width: 1.3rem; height: 0.8rem; cursor: pointer; position: absolute; top: 0.1rem; left: 0.1rem; z-index: 1; background: ${vt.checkboxOff};
     border-radius: var(--rounded); transition: left 0.6s ease; }
 
   input[type=checkbox] { visibility: hidden; }
-  input[type=checkbox]:checked + label { left: 1.4rem; background: ${kt.checkboxOn}; }
+  input[type=checkbox]:checked + label { left: 1.4rem; background: ${vt.checkboxOn}; }
 
-  .menu-range { margin: 0.2rem 0.5rem 0 0; width: 3.5rem; background: transparent; color: ${kt.rangeBackground}; }
-  .menu-range:before { color: ${kt.rangeLabel}; margin: 0 0.4rem 0 0; font-weight: 800; font-size: 0.6rem; position: relative; top: 0.3rem; content: attr(value); }
+  .menu-range { margin: 0.2rem 0.5rem 0 0; width: 3.5rem; background: transparent; color: ${vt.rangeBackground}; }
+  .menu-range:before { color: ${vt.rangeLabel}; margin: 0 0.4rem 0 0; font-weight: 800; font-size: 0.6rem; position: relative; top: 0.3rem; content: attr(value); }
 
   input[type=range] { -webkit-appearance: none; }
-  input[type=range]::-webkit-slider-runnable-track { width: 100%; height: 1rem; cursor: pointer; background: ${kt.itemBackground}; border-radius: var(--rounded); border: 1px; }
-  input[type=range]::-moz-range-track { width: 100%; height: 1rem; cursor: pointer; background: ${kt.itemBackground}; border-radius: var(--rounded); border: 1px; }
-  input[type=range]::-webkit-slider-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${kt.rangeBackground}; cursor: pointer; -webkit-appearance: none; }
-  input[type=range]::-moz-range-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${kt.rangeBackground}; cursor: pointer; -webkit-appearance: none; }
+  input[type=range]::-webkit-slider-runnable-track { width: 100%; height: 1rem; cursor: pointer; background: ${vt.itemBackground}; border-radius: var(--rounded); border: 1px; }
+  input[type=range]::-moz-range-track { width: 100%; height: 1rem; cursor: pointer; background: ${vt.itemBackground}; border-radius: var(--rounded); border: 1px; }
+  input[type=range]::-webkit-slider-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${vt.rangeBackground}; cursor: pointer; -webkit-appearance: none; }
+  input[type=range]::-moz-range-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${vt.rangeBackground}; cursor: pointer; -webkit-appearance: none; }
 
   .svg-background { fill:darkslategrey; cursor:pointer; opacity: 0.6; }
   .svg-foreground { fill:white; cursor:pointer; opacity: 0.8; }
-  `,t=document.createElement("style");t.innerHTML=e,document.getElementsByTagName("head")[0].appendChild(t),q4=!0}var X4=class{constructor(t,n,r,a){a&&(kt={...kt,...a}),zse(),this.createMenu(t,n,r),this.id=0,this.instance=nh,nh++,this._maxFPS=0,this.hidden=0}createMenu(t,n="",r={top:null,left:null,bottom:null,right:null}){this.menu=document.createElement("div"),this.menu.id=`menu-${nh}`,this.menu.className="menu",r&&(r.top&&(this.menu.style.top=r.top),r.bottom&&(this.menu.style.bottom=r.bottom),r.left&&(this.menu.style.left=r.left),r.right&&(this.menu.style.right=r.right)),this.container=document.createElement("div"),this.container.id=`menu-container-${nh}`,this.container.className="menu-container menu-container-fadein";let a=document.createElement("div");a.className="menu-title",a.id=`menu-title-${nh}`;let s=`<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512" style="width: 2rem; height: 2rem; vertical-align: top;">
+  `,t=document.createElement("style");t.innerHTML=e,document.getElementsByTagName("head")[0].appendChild(t),X4=!0}var K4=class{constructor(t,n,r,a){a&&(vt={...vt,...a}),Ese(),this.createMenu(t,n,r),this.id=0,this.instance=rh,rh++,this._maxFPS=0,this.hidden=0}createMenu(t,n="",r={top:null,left:null,bottom:null,right:null}){this.menu=document.createElement("div"),this.menu.id=`menu-${rh}`,this.menu.className="menu",r&&(r.top&&(this.menu.style.top=r.top),r.bottom&&(this.menu.style.bottom=r.bottom),r.left&&(this.menu.style.left=r.left),r.right&&(this.menu.style.right=r.right)),this.container=document.createElement("div"),this.container.id=`menu-container-${rh}`,this.container.className="menu-container menu-container-fadein";let a=document.createElement("div");a.className="menu-title",a.id=`menu-title-${rh}`;let s=`<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512" style="width: 2rem; height: 2rem; vertical-align: top;">
         <path d="M400 32H48A48 48 0 0 0 0 80v352a48 48 0 0 0 48 48h352a48 48 0 0 0 48-48V80a48 48 0 0 0-48-48zm-51.37 182.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z" class="svg-background"/>
         <path d="M348.63 214.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z" class="svg-foreground"/>
-      </svg>`;n&&(a.innerHTML=`${n}${s}`),this.menu.appendChild(a),a.addEventListener("click",()=>{this.container.classList.toggle("menu-container-fadeout"),this.container.classList.toggle("menu-container-fadein"),this.menu.style.borderStyle=this.container.classList.contains("menu-container-fadeout")?"none":"solid"}),this.menu.appendChild(this.container),typeof t=="object"?t.appendChild(this.menu):document.getElementById(t).appendChild(this.menu)}get newID(){return this.id++,`menu-${this.instance}-${this.id}`}get ID(){return`menu-${this.instance}-${this.id}`}get width(){return this.menu.offsetWidth}get height(){return this.menu.offsetHeight}hide(){this.container.classList.contains("menu-container-fadein")&&(this.container.classList.toggle("menu-container-fadeout"),this.container.classList.toggle("menu-container-fadein"))}visible(){return 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o=this.cpuAccums[i]/r*100,l=this.gpuAccums[i]/r*100,u=performance&&performance.memory?performance.memory.usedJSHeapSize/(1<<20):0;this.paramLogger(i,o,l,u,s,r,a),this.cpuAccums[i]=0,Promise.all(this.finished).then(()=>{this.gpuAccums[i]=0,this.finished=[]})}this.paramFrame=this.frameId,this.paramTime=n}}if(!this.detected||!this.chartFrame)this.chartFrame=this.frameId,this.chartTime=n,this.circularId=0;else{let r=n-this.chartTime,a=this.chartHz*r/1e3;for(;--a>0&&this.detected;){let i=(this.frameId-this.chartFrame)/r*1e3;this.chart[this.circularId%this.chartLen]=i;for(let o=0;o<this.names.length;o++)this.chartLogger(o,this.chart,this.circularId);this.circularId++,this.chartFrame=this.frameId,this.chartTime=n}}}begin(t){this.updateAccums(t)}end(t){this.updateAccums(t)}updateAccums(t){let n=this.names.indexOf(t);n===-1&&(n=this.names.length,this.addUI(t));let r=this.now(),a=r-this.t0;for(let 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     backend: ${te.tf.getBackend()} | ${i}<br>
-    performance: ${Wse(t.performance)}ms FPS process:${l} refresh:${u}<br>
+    performance: ${Fse(t.performance)}ms FPS process:${l} refresh:${u}<br>
     ${c}<br>
-  `,he.framesDraw++,he.lastFrame=performance.now(),he.buffered?he.drawThread=requestAnimationFrame(()=>J0(e,n)):!he.buffered&&he.drawThread&&(qn("stopping buffered refresh"),cancelAnimationFrame(he.drawThread),he.drawThread=null)}async function Q0(){var u;if(he.busy)return null;he.busy=!0;let e=document.getElementById("video"),t=document.getElementById("canvas"),n=document.getElementById("log"),r=e.srcObject?e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState>2&&!e.paused:!1,a="";if(ar("setting up camera"),!navigator.mediaDevices)return a="camera access not supported",n.innerText+=`
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 ${a}`,qn(a),ar(a),he.busy=!1,a;let s,i={audio:!1,video:{facingMode:he.facing?"user":"environment",resizeMode:he.crop?"crop-and-scale":"none"}};window.innerWidth>window.innerHeight?i.video.width={ideal:window.innerWidth}:i.video.height={ideal:window.innerHeight-document.getElementById("menubar").offsetHeight};try{s=await navigator.mediaDevices.getUserMedia(i)}catch(c){return c.name==="PermissionDeniedError"||c.name==="NotAllowedError"?a="camera permission denied":c.name==="SourceUnavailableError"?a="camera not available":a=`camera error: ${c.message||c}`,n.innerText+=`
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-Human error: ${s.error}`):(Y0=s,he.drawThread||J0(e),he.framesDetect++,he.detectThread=requestAnimationFrame(i=>ah(e,t,i)))})}async function Use(e){return new Promise(t=>{let n=new Image;n.onload=async()=>{qn("Processing image:",encodeURI(n.src));let r=document.getElementById("canvas");n.width=n.naturalWidth,n.height=n.naturalHeight,r.width=te.config.filter.width&&te.config.filter.width>0?te.config.filter.width:n.naturalWidth,r.height=te.config.filter.height&&te.config.filter.height>0?te.config.filter.height:n.naturalHeight;let a=await te.detect(n,us);Y0=a,await J0(n);let s=document.createElement("canvas");s.className="thumbnail",s.width=window.innerWidth/(he.columns+.1),s.height=s.width*r.height/r.width,a.face&&a.face.length>0?s.title=a.face.map((o,l)=>`#${l} face: ${Math.trunc(100*o.faceConfidence)}% box: ${Math.trunc(100*o.boxConfidence)}% age: ${Math.trunc(o.age)} gender: ${Math.trunc(100*o.genderConfidence)}% ${o.gender}`).join(" | "):s.title="no face detected",s.getContext("2d").drawImage(r,0,0,r.width,r.height,0,0,s.width,s.height),document.getElementById("samples-container").appendChild(s),n.src="",t(!0)},n.src=e})}async function Q4(){document.getElementById("samples-container").style.display="none",document.getElementById("canvas").style.display="block";let e=document.getElementById("video"),t=document.getElementById("canvas");if(e.srcObject!==null&&!e.paused)document.getElementById("play").style.display="block",document.getElementById("btnStart").className="button button-start",document.getElementById("btnStart").innerHTML="start<br>video",ar("paused"),e.pause();else{let n=await Q0();if(n)ar(n);else{document.getElementById("play").style.display="none";for(let r of Object.values(Ae))r.hide();ar(""),document.getElementById("btnStart").className="button button-stop",document.getElementById("btnStart").innerHTML="pause<br>video",await e.play(),he.detectThread||ah(e,t)}}}async function Hse(){us.videoOptimized=!1,document.getElementById("play").style.display="none",document.getElementById("canvas").style.display="none",document.getElementById("samples-container").style.display="block",qn("Running detection of sample images"),ar("processing images"),document.getElementById("samples-container").innerHTML="";for(let e of Object.values(Ae))e.hide();for(let e of he.samples)await Use(e);ar("")}function jse(){let e=[];window.innerWidth>800?e=[`${document.getElementById("btnDisplay").offsetLeft-50}px`,`${document.getElementById("btnImage").offsetLeft-50}px`,`${document.getElementById("btnProcess").offsetLeft-50}px`,`${document.getElementById("btnModel").offsetLeft-50}px`]:e=["0rem","11rem","21.1rem","33rem"],Ae.display=new rh(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[0]}),Ae.display.addBool("perf monitor",he,"bench",t=>he.bench=t),Ae.display.addBool("buffered output",he,"buffered",t=>he.buffered=t),Ae.display.addBool("crop & scale",he,"crop",t=>{he.crop=t,Q0()}),Ae.display.addBool("camera facing",he,"facing",t=>{he.facing=t,Q0()}),Ae.display.addHTML('<hr style="border-style: inset; 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border-color: dimgray">'),Ae.process.addButton("process sample images","process images",()=>Hse()),Ae.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.process.addChart("FPS","FPS"),Ae.models=new rh(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[3]}),Ae.models.addBool("face detect",te.config.face,"enabled",t=>te.config.face.enabled=t),Ae.models.addBool("face mesh",te.config.face.mesh,"enabled",t=>te.config.face.mesh.enabled=t),Ae.models.addBool("face iris",te.config.face.iris,"enabled",t=>te.config.face.iris.enabled=t),Ae.models.addBool("face age",te.config.face.age,"enabled",t=>te.config.face.age.enabled=t),Ae.models.addBool("face gender",te.config.face.gender,"enabled",t=>te.config.face.gender.enabled=t),Ae.models.addBool("face emotion",te.config.face.emotion,"enabled",t=>te.config.face.emotion.enabled=t),Ae.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.models.addBool("body pose",te.config.body,"enabled",t=>te.config.body.enabled=t),Ae.models.addBool("hand pose",te.config.hand,"enabled",t=>te.config.hand.enabled=t),Ae.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.models.addBool("gestures",te.config.gesture,"enabled",t=>te.config.gesture.enabled=t),Ae.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.models.addBool("object detection",te.config.object,"enabled",t=>te.config.object.enabled=t),Ae.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.models.addBool("face compare",te.config.face.embedding,"enabled",t=>{te.config.face.embedding.enabled=t,Hi=null}),document.getElementById("btnDisplay").addEventListener("click",t=>Ae.display.toggle(t)),document.getElementById("btnImage").addEventListener("click",t=>Ae.image.toggle(t)),document.getElementById("btnProcess").addEventListener("click",t=>Ae.process.toggle(t)),document.getElementById("btnModel").addEventListener("click",t=>Ae.models.toggle(t)),document.getElementById("btnStart").addEventListener("click",()=>Q4()),document.getElementById("play").addEventListener("click",()=>Q4())}async function Gse(e){let t=document.getElementById("canvas");t.width=e.canvas.width,t.height=e.canvas.height,t.getContext("2d").drawImage(e.canvas,0,0,e.canvas.width,e.canvas.height,0,0,t.width,t.height),await te.draw.all(t,e)}async function qse(){if(qn("Demo starting ..."),jse(),document.getElementById("log").innerText=`Human: version ${te.version}`,he.modelsPreload&&!he.useWorker){ar("loading"),await te.load(us);let e=Object.keys(te.models).filter(t=>te.models[t]);qn("Demo loaded models:",e)}if(!he.useWorker){ar("initializing");let e=await te.warmup(us);e&&e.canvas&&he.drawWarmup&&await Gse(e)}ar("human: ready"),document.getElementById("loader").style.display="none",document.getElementById("play").style.display="block",qn("Demo ready...")}window.onload=qse;window.onresize=Q0;
+${a}`,ar(a),qn("camera error:",c),he.busy=!1,a}if(s)e.srcObject=s;else return he.busy=!1,"camera stream empty";let o=s.getVideoTracks()[0],l=o.getSettings();return he.camera={name:(u=o.label)==null?void 0:u.toLowerCase(),width:l.width,height:l.height,facing:l.facingMode==="user"?"front":"back"},new Promise(c=>{e.onloadeddata=async()=>{e.width=e.videoWidth,e.height=e.videoHeight,t.width=e.width,t.height=e.height,t.style.width=t.width>t.height?"100vw":"",t.style.height=t.width>t.height?"":"100vh",he.menuWidth.input.setAttribute("value",e.width),he.menuHeight.input.setAttribute("value",e.height),r&&e.play(),r&&!he.detectThread&&sh(e,t),he.busy=!1,ar(""),c()}})}function Q4(){if(!Ui){let e=null;Ui=new Y4(e,{trackGPU:!1,chartHz:20,chartLen:20}),Ui.begin()}}function $se(e,t,n,r){Y0||(qn("creating worker thread"),Y0=new Worker(he.worker,{type:"module"}),Y0.addEventListener("message",a=>{a.data.result.performance&&a.data.result.performance.total&&he.detectFPS.push(1e3/a.data.result.performance.total),he.detectFPS.length>he.maxFPSframes&&he.detectFPS.shift(),he.bench&&(Ui||Q4(),Ui.nextFrame(r)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=he.bench?"block":"none"),J0=a.data.result,he.framesDetect++,he.drawThread||Q0(e),he.detectThread=requestAnimationFrame(s=>sh(e,n,s))})),Y0.postMessage({image:t.data.buffer,width:n.width,height:n.height,userConfig:us},[t.data.buffer])}function sh(e,t,n){var a;if(!(e.srcObject&&e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState>2&&!e.paused)&&e.srcObject){he.drawThread&&cancelAnimationFrame(he.drawThread),he.detectThread&&cancelAnimationFrame(he.detectThread),he.drawThread=null,he.detectThread=null,e.paused?qn("camera paused"):e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState<=2?setTimeout(()=>sh(e,t),500):qn(`camera not ready: track state: ${(a=e.srcObject)==null?void 0:a.getVideoTracks()[0].readyState} stream state: ${e.readyState}`),clearTimeout(he.drawThread),he.drawThread=null,qn("frame statistics: process:",he.framesDetect,"refresh:",he.framesDraw),qn("memory",te.tf.engine().memory());return}if(ar(""),he.useWorker){let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(t.width,t.height):document.createElement("canvas");s.width=t.width,s.height=t.height;let i=s.getContext("2d");i.drawImage(e,0,0,e.width,e.height,0,0,t.width,t.height);let o=i.getImageData(0,0,t.width,t.height);$se(e,o,t,us,n)}else te.detect(e,us).then(s=>{s.performance&&s.performance.total&&he.detectFPS.push(1e3/s.performance.total),he.detectFPS.length>he.maxFPSframes&&he.detectFPS.shift(),he.bench&&(Ui||Q4(),Ui.nextFrame(n)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=he.bench?"block":"none"),s.error?(qn(s.error),document.getElementById("log").innerText+=`
+Human error: ${s.error}`):(J0=s,he.drawThread||Q0(e),he.framesDetect++,he.detectThread=requestAnimationFrame(i=>sh(e,t,i)))})}async function Dse(e){return new Promise(t=>{let n=new Image;n.onload=async()=>{qn("Processing image:",encodeURI(n.src));let r=document.getElementById("canvas");n.width=n.naturalWidth,n.height=n.naturalHeight,r.width=te.config.filter.width&&te.config.filter.width>0?te.config.filter.width:n.naturalWidth,r.height=te.config.filter.height&&te.config.filter.height>0?te.config.filter.height:n.naturalHeight;let a=await te.detect(n,us);J0=a,await Q0(n);let s=document.createElement("canvas");s.className="thumbnail",s.width=window.innerWidth/(he.columns+.1),s.height=s.width*r.height/r.width,a.face&&a.face.length>0?s.title=a.face.map((o,l)=>`#${l} face: ${Math.trunc(100*o.faceConfidence)}% box: ${Math.trunc(100*o.boxConfidence)}% age: ${Math.trunc(o.age)} gender: ${Math.trunc(100*o.genderConfidence)}% ${o.gender}`).join(" | "):s.title="no face detected",s.getContext("2d").drawImage(r,0,0,r.width,r.height,0,0,s.width,s.height),document.getElementById("samples-container").appendChild(s),n.src="",t(!0)},n.src=e})}async function e8(){document.getElementById("samples-container").style.display="none",document.getElementById("canvas").style.display="block";let e=document.getElementById("video"),t=document.getElementById("canvas");if(e.srcObject!==null&&!e.paused)document.getElementById("play").style.display="block",document.getElementById("btnStart").className="button button-start",document.getElementById("btnStart").innerHTML="start<br>video",ar("paused"),e.pause();else{let n=await e1();if(n)ar(n);else{document.getElementById("play").style.display="none";for(let r of Object.values(Ae))r.hide();ar(""),document.getElementById("btnStart").className="button button-stop",document.getElementById("btnStart").innerHTML="pause<br>video",await e.play(),he.detectThread||sh(e,t)}}}async function Ose(){us.videoOptimized=!1,document.getElementById("play").style.display="none",document.getElementById("canvas").style.display="none",document.getElementById("samples-container").style.display="block",qn("Running detection of sample images"),ar("processing images"),document.getElementById("samples-container").innerHTML="";for(let e of Object.values(Ae))e.hide();for(let e of he.samples)await Dse(e);ar("")}function zse(){let e=[];window.innerWidth>800?e=[`${document.getElementById("btnDisplay").offsetLeft-50}px`,`${document.getElementById("btnImage").offsetLeft-50}px`,`${document.getElementById("btnProcess").offsetLeft-50}px`,`${document.getElementById("btnModel").offsetLeft-50}px`]:e=["0rem","11rem","21.1rem","33rem"],Ae.display=new ah(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[0]}),Ae.display.addBool("perf monitor",he,"bench",t=>he.bench=t),Ae.display.addBool("buffered output",he,"buffered",t=>he.buffered=t),Ae.display.addBool("crop & scale",he,"crop",t=>{he.crop=t,e1()}),Ae.display.addBool("camera facing",he,"facing",t=>{he.facing=t,e1()}),Ae.display.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.display.addBool("use 3D depth",te.draw.drawOptions,"useDepth"),Ae.display.addBool("draw with curves",te.draw.drawOptions,"useCurves"),Ae.display.addBool("print labels",te.draw.drawOptions,"drawLabels"),Ae.display.addBool("draw points",te.draw.drawOptions,"drawPoints"),Ae.display.addBool("draw boxes",te.draw.drawOptions,"drawBoxes"),Ae.display.addBool("draw polygons",te.draw.drawOptions,"drawPolygons"),Ae.display.addBool("fill polygons",te.draw.drawOptions,"fillPolygons"),Ae.image=new ah(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[1]}),Ae.image.addBool("enabled",te.config.filter,"enabled",t=>te.config.filter.enabled=t),he.menuWidth=Ae.image.addRange("image width",te.config.filter,"width",0,3840,10,t=>te.config.filter.width=parseInt(t)),he.menuHeight=Ae.image.addRange("image height",te.config.filter,"height",0,2160,10,t=>te.config.filter.height=parseInt(t)),Ae.image.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.image.addRange("brightness",te.config.filter,"brightness",-1,1,.05,t=>te.config.filter.brightness=parseFloat(t)),Ae.image.addRange("contrast",te.config.filter,"contrast",-1,1,.05,t=>te.config.filter.contrast=parseFloat(t)),Ae.image.addRange("sharpness",te.config.filter,"sharpness",0,1,.05,t=>te.config.filter.sharpness=parseFloat(t)),Ae.image.addRange("blur",te.config.filter,"blur",0,20,1,t=>te.config.filter.blur=parseInt(t)),Ae.image.addRange("saturation",te.config.filter,"saturation",-1,1,.05,t=>te.config.filter.saturation=parseFloat(t)),Ae.image.addRange("hue",te.config.filter,"hue",0,360,5,t=>te.config.filter.hue=parseInt(t)),Ae.image.addRange("pixelate",te.config.filter,"pixelate",0,32,1,t=>te.config.filter.pixelate=parseInt(t)),Ae.image.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.image.addBool("negative",te.config.filter,"negative",t=>te.config.filter.negative=t),Ae.image.addBool("sepia",te.config.filter,"sepia",t=>te.config.filter.sepia=t),Ae.image.addBool("vintage",te.config.filter,"vintage",t=>te.config.filter.vintage=t),Ae.image.addBool("kodachrome",te.config.filter,"kodachrome",t=>te.config.filter.kodachrome=t),Ae.image.addBool("technicolor",te.config.filter,"technicolor",t=>te.config.filter.technicolor=t),Ae.image.addBool("polaroid",te.config.filter,"polaroid",t=>te.config.filter.polaroid=t),Ae.process=new ah(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[2]}),Ae.process.addList("backend",["cpu","webgl","wasm","humangl"],te.config.backend,t=>te.config.backend=t),Ae.process.addBool("async operations",te.config,"async",t=>te.config.async=t),Ae.process.addBool("use web worker",he,"useWorker"),Ae.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.process.addLabel("model parameters"),Ae.process.addRange("max objects",te.config.face.detector,"maxFaces",1,50,1,t=>{te.config.face.detector.maxFaces=parseInt(t),te.config.body.maxDetections=parseInt(t),te.config.hand.maxHands=parseInt(t)}),Ae.process.addRange("skip frames",te.config.face.detector,"skipFrames",0,50,1,t=>{te.config.face.detector.skipFrames=parseInt(t),te.config.face.emotion.skipFrames=parseInt(t),te.config.face.age.skipFrames=parseInt(t),te.config.hand.skipFrames=parseInt(t)}),Ae.process.addRange("min confidence",te.config.face.detector,"minConfidence",0,1,.05,t=>{te.config.face.detector.minConfidence=parseFloat(t),te.config.face.gender.minConfidence=parseFloat(t),te.config.face.emotion.minConfidence=parseFloat(t),te.config.hand.minConfidence=parseFloat(t)}),Ae.process.addRange("score threshold",te.config.face.detector,"scoreThreshold",.1,1,.05,t=>{te.config.face.detector.scoreThreshold=parseFloat(t),te.config.hand.scoreThreshold=parseFloat(t),te.config.body.scoreThreshold=parseFloat(t)}),Ae.process.addRange("overlap",te.config.face.detector,"iouThreshold",.1,1,.05,t=>{te.config.face.detector.iouThreshold=parseFloat(t),te.config.hand.iouThreshold=parseFloat(t)}),Ae.process.addBool("detection rotation",te.config.face.detector,"rotation",t=>{te.config.face.detector.rotation=t,te.config.hand.rotation=t}),Ae.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.process.addButton("process sample images","process images",()=>Ose()),Ae.process.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.process.addChart("FPS","FPS"),Ae.models=new ah(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[3]}),Ae.models.addBool("face detect",te.config.face,"enabled",t=>te.config.face.enabled=t),Ae.models.addBool("face mesh",te.config.face.mesh,"enabled",t=>te.config.face.mesh.enabled=t),Ae.models.addBool("face iris",te.config.face.iris,"enabled",t=>te.config.face.iris.enabled=t),Ae.models.addBool("face age",te.config.face.age,"enabled",t=>te.config.face.age.enabled=t),Ae.models.addBool("face gender",te.config.face.gender,"enabled",t=>te.config.face.gender.enabled=t),Ae.models.addBool("face emotion",te.config.face.emotion,"enabled",t=>te.config.face.emotion.enabled=t),Ae.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.models.addBool("body pose",te.config.body,"enabled",t=>te.config.body.enabled=t),Ae.models.addBool("hand pose",te.config.hand,"enabled",t=>te.config.hand.enabled=t),Ae.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.models.addBool("gestures",te.config.gesture,"enabled",t=>te.config.gesture.enabled=t),Ae.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.models.addBool("object detection",te.config.object,"enabled",t=>te.config.object.enabled=t),Ae.models.addHTML('<hr style="border-style: inset; border-color: dimgray">'),Ae.models.addBool("face compare",te.config.face.embedding,"enabled",t=>{te.config.face.embedding.enabled=t,ji=null}),document.getElementById("btnDisplay").addEventListener("click",t=>Ae.display.toggle(t)),document.getElementById("btnImage").addEventListener("click",t=>Ae.image.toggle(t)),document.getElementById("btnProcess").addEventListener("click",t=>Ae.process.toggle(t)),document.getElementById("btnModel").addEventListener("click",t=>Ae.models.toggle(t)),document.getElementById("btnStart").addEventListener("click",()=>e8()),document.getElementById("play").addEventListener("click",()=>e8())}async function Pse(e){let t=document.getElementById("canvas");t.width=e.canvas.width,t.height=e.canvas.height,t.getContext("2d").drawImage(e.canvas,0,0,e.canvas.width,e.canvas.height,0,0,t.width,t.height),await te.draw.all(t,e)}async function Lse(){if(qn("Demo starting ..."),zse(),document.getElementById("log").innerText=`Human: version ${te.version}`,he.modelsPreload&&!he.useWorker){ar("loading"),await te.load(us);let e=Object.keys(te.models).filter(t=>te.models[t]);qn("Demo loaded models:",e)}if(!he.useWorker){ar("initializing");let e=await te.warmup(us);e&&e.canvas&&he.drawWarmup&&await Pse(e)}ar("human: ready"),document.getElementById("loader").style.display="none",document.getElementById("play").style.display="block",qn("Demo ready...")}window.onload=Lse;window.onresize=e1;
 /**
  * @license
  * Copyright 2017 Google LLC. All Rights Reserved.
diff --git a/dist/demo-browser-index.js.map b/dist/demo-browser-index.js.map
index 3501452b..9b737cf6 100644
--- a/dist/demo-browser-index.js.map
+++ b/dist/demo-browser-index.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
-  "sources": ["../src/blazeface/facemesh.ts", "../src/posenet/keypoints.ts", "../src/log.ts", "../src/sysinfo.ts", "../node_modules/node-fetch/browser.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/alea.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xor128.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xorwow.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xorshift7.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xor4096.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/tychei.js", "(disabled):crypto", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/seedrandom.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/index.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/alea.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xor128.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xorwow.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xorshift7.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xor4096.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/tychei.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/seedrandom.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/index.js", "(disabled):path", "(disabled):worker_threads", "(disabled):perf_hooks", "../node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js", "../node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js", "../node_modules/seedrandom/lib/alea.js", "../node_modules/seedrandom/lib/xor128.js", "../node_modules/seedrandom/lib/xorwow.js", "../node_modules/seedrandom/lib/xorshift7.js", "../node_modules/seedrandom/lib/xor4096.js", 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"../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/basic_math.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/control.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/convolution.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/creation.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/dynamic.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/evaluation.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/graph.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/hash_table.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/image.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/logical.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/matrices.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/normalization.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/reduction.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/slice_join.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/spectral.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/op_list/transformation.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/operation_mapper.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/custom_op/node_value_impl.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/arithmetic_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/basic_math_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/executor/tensor_utils.ts", "../node_modules/@tensorflow/tfjs-converter/src/executor/tensor_array.ts", "../node_modules/@tensorflow/tfjs-converter/src/executor/tensor_list.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/control_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/convolution_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/creation_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/dynamic_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/evaluation_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/graph_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/executor/hash_table.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/hash_table_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/image_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/logical_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/matrices_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/normalization_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/reduction_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/slice_join_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/spectral_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/executors/transformation_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/operations/operation_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/executor/execution_context.ts", "../node_modules/@tensorflow/tfjs-converter/src/executor/model_analysis.ts", "../node_modules/@tensorflow/tfjs-converter/src/executor/graph_executor.ts", "../node_modules/@tensorflow/tfjs-converter/src/executor/resource_manager.ts", "../node_modules/@tensorflow/tfjs-converter/src/executor/graph_model.ts", "../node_modules/@tensorflow/tfjs-converter/src/version.ts", "../node_modules/@tensorflow/tfjs-converter/src/index.ts", "../node_modules/@tensorflow/tfjs-data/src/index.ts", "../node_modules/@tensorflow/tfjs-data/src/dataset.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/lazy_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/util/deep_map.ts", "../node_modules/@tensorflow/tfjs-data/src/util/deep_clone.ts", "../node_modules/@tensorflow/tfjs-data/src/util/ring_buffer.ts", "../node_modules/@tensorflow/tfjs-data/src/util/growing_ring_buffer.ts", "../node_modules/@tensorflow/tfjs-data/src/datasets/text_line_dataset.ts", "../node_modules/@tensorflow/tfjs-data/src/datasets/csv_dataset.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/microphone_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/webcam_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/datasource.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/string_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/byte_chunk_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/file_chunk_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/url_chunk_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/util/source_util.ts", "../node_modules/@tensorflow/tfjs-data/src/sources/file_data_source.ts", "../node_modules/@tensorflow/tfjs-data/src/sources/url_data_source.ts", "../node_modules/@tensorflow/tfjs-data/src/readers.ts", "../node_modules/@tensorflow/tfjs-data/src/version.ts", "../src/tfjs/tf-browser.ts", "../src/tfjs/backend.ts", "../src/blazeface/blazeface.ts", "../src/blazeface/box.ts", "../src/blazeface/util.ts", "../src/blazeface/coords.ts", "../src/blazeface/facepipeline.ts", "../src/human.ts", "../src/age/age.ts", "../src/profile.ts", "../src/gender/gender.ts", "../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/decodePose.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/box.ts", "../src/handpose/handdetector.ts", "../src/handpose/util.ts", "../src/handpose/handpipeline.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/nanodet/nanodet.ts", "../src/gesture/gesture.ts", "../src/imagefx.js", "../src/image.ts", "../config.ts", "../src/sample.ts", "../src/draw.ts", "../demo/menu.js", "../demo/gl-bench.js", "../demo/browser.js"],
-  "sourcesContent": ["import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - prediction.box.startPoint[0],\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - prediction.box.startPoint[1],\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0] / input.shape[2]),\n        Math.max(0, prediction.box.startPoint[1] / input.shape[1]),\n        Math.min(input.shape[1], (prediction.box.endPoint[0]) - prediction.box.startPoint[0]) / input.shape[2],\n        Math.min(input.shape[2], (prediction.box.endPoint[1]) - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        mesh,\n        boxRaw,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 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ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){err(\"requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];var contextAttributes={\"alpha\":!!GROWABLE_HEAP_I32()[a+(0>>2)],\"depth\":!!GROWABLE_HEAP_I32()[a+(4>>2)],\"stencil\":!!GROWABLE_HEAP_I32()[a+(8>>2)],\"antialias\":!!GROWABLE_HEAP_I32()[a+(12>>2)],\"premultipliedAlpha\":!!GROWABLE_HEAP_I32()[a+(16>>2)],\"preserveDrawingBuffer\":!!GROWABLE_HEAP_I32()[a+(20>>2)],\"powerPreference\":__emscripten_webgl_power_preferences[powerPreference],\"failIfMajorPerformanceCaveat\":!!GROWABLE_HEAP_I32()[a+(28>>2)],majorVersion:GROWABLE_HEAP_I32()[a+(32>>2)],minorVersion:GROWABLE_HEAP_I32()[a+(36>>2)],enableExtensionsByDefault:GROWABLE_HEAP_I32()[a+(40>>2)],explicitSwapControl:GROWABLE_HEAP_I32()[a+(44>>2)],proxyContextToMainThread:GROWABLE_HEAP_I32()[a+(48>>2)],renderViaOffscreenBackBuffer:GROWABLE_HEAP_I32()[a+(52>>2)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var 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\"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,HEAPU8,outPtr,maxBytesToWrite)}function writeArrayToMemory(array,buffer){HEAP8.set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;__ATINIT__.push({func:function(){___wasm_call_ctors()}});function preRun(){if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=HEAP32[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){}function _fd_write(fd,iov,iovcnt,pnum){var num=0;for(var i=0;i<iovcnt;i++){var ptr=HEAP32[iov+i*8>>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j])}num+=len}HEAP32[pnum>>2]=num;return 0}var asmLibraryArg={\"a\":_abort,\"d\":_emscripten_memcpy_big,\"e\":_emscripten_resize_heap,\"f\":_fd_close,\"c\":_fd_seek,\"b\":_fd_write};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"h\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"i\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"j\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"k\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"l\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"n\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"o\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"p\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"q\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"r\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"s\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"t\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"u\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"v\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"w\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"x\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"y\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"z\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"F\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var 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_Rsqrt=Module[\"_Rsqrt\"]=function(){return(_Rsqrt=Module[\"_Rsqrt\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var _ScatterNd=Module[\"_ScatterNd\"]=function(){return(_ScatterNd=Module[\"_ScatterNd\"]=Module[\"asm\"][\"qa\"]).apply(null,arguments)};var _SelectV2=Module[\"_SelectV2\"]=function(){return(_SelectV2=Module[\"_SelectV2\"]=Module[\"asm\"][\"ra\"]).apply(null,arguments)};var _Sigmoid=Module[\"_Sigmoid\"]=function(){return(_Sigmoid=Module[\"_Sigmoid\"]=Module[\"asm\"][\"sa\"]).apply(null,arguments)};var _Sin=Module[\"_Sin\"]=function(){return(_Sin=Module[\"_Sin\"]=Module[\"asm\"][\"ta\"]).apply(null,arguments)};var _Softmax=Module[\"_Softmax\"]=function(){return(_Softmax=Module[\"_Softmax\"]=Module[\"asm\"][\"ua\"]).apply(null,arguments)};var _Sqrt=Module[\"_Sqrt\"]=function(){return(_Sqrt=Module[\"_Sqrt\"]=Module[\"asm\"][\"va\"]).apply(null,arguments)};var _Square=Module[\"_Square\"]=function(){return(_Square=Module[\"_Square\"]=Module[\"asm\"][\"wa\"]).apply(null,arguments)};var _SquaredDifference=Module[\"_SquaredDifference\"]=function(){return(_SquaredDifference=Module[\"_SquaredDifference\"]=Module[\"asm\"][\"xa\"]).apply(null,arguments)};var _Step=Module[\"_Step\"]=function(){return(_Step=Module[\"_Step\"]=Module[\"asm\"][\"ya\"]).apply(null,arguments)};var _StridedSlice=Module[\"_StridedSlice\"]=function(){return(_StridedSlice=Module[\"_StridedSlice\"]=Module[\"asm\"][\"za\"]).apply(null,arguments)};var _Sub=Module[\"_Sub\"]=function(){return(_Sub=Module[\"_Sub\"]=Module[\"asm\"][\"Aa\"]).apply(null,arguments)};var _Sum=Module[\"_Sum\"]=function(){return(_Sum=Module[\"_Sum\"]=Module[\"asm\"][\"Ba\"]).apply(null,arguments)};var _Tanh=Module[\"_Tanh\"]=function(){return(_Tanh=Module[\"_Tanh\"]=Module[\"asm\"][\"Ca\"]).apply(null,arguments)};var _Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(e){try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 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0.883246004581451],\n  [0.508952975273132, 0.579437971115112],\n  [0.617941975593567, 0.508316040039062],\n  [0.825608015060425, 0.397674977779388],\n  [0.681214988231659, 0.39623498916626],\n  [0.656635999679565, 0.400596976280212],\n  [0.603900015354156, 0.710216999053955],\n  [0.81208598613739, 0.588539004325867],\n  [0.56801301240921, 0.944564998149872],\n  [0.681007981300354, 0.898285031318665],\n  [0.733752012252808, 0.869701027870178],\n  [0.633830010890961, 0.398822009563446],\n  [0.606792986392975, 0.39553701877594],\n  [0.589659988880157, 0.391062021255493],\n  [0.805015981197357, 0.342108011245728],\n  [0.611334979534149, 0.362284004688263],\n  [0.634037971496582, 0.355970978736877],\n  [0.656635999679565, 0.355356991291046],\n  [0.681214988231659, 0.35834002494812],\n  [0.698584973812103, 0.363156020641327],\n  [0.941866993904114, 0.319076001644135],\n  [0.698584973812103, 0.387449026107788],\n  [0.584177017211914, 0.624107003211975],\n  [0.554318010807037, 0.566076993942261],\n  [0.534153997898102, 0.62064003944397],\n  [0.711217999458313, 0.819975018501282],\n  [0.664629995822906, 0.852871000766754],\n  [0.559099972248077, 0.902631998062134],\n  [0.871706008911133, 0.791940987110138],\n  [0.591234028339386, 0.373893976211548],\n  [0.544341027736664, 0.451583981513977],\n  [0.624562978744507, 0.924192011356354],\n  [0.88577002286911, 0.615028977394104],\n  [0.551338016986847, 0.695277988910675],\n  [0.551980018615723, 0.704632043838501],\n  [0.552887976169586, 0.715808033943176],\n  [0.555167973041534, 0.730794012546539],\n  [0.569944024085999, 0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      resolve({ face: faceRes, body: bodyRes, hand: handRes, gesture: gestureRes, object: objectRes, performance: this.#perf, canvas: process.canvas });\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - prediction.box.topLeft[0],\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - prediction.box.topLeft[1],\n      ] : 0;\n      hands.push({ confidence: prediction.confidence, box, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            boxRaw[0] * outputShape[0],\n            boxRaw[1] * outputShape[1],\n            boxRaw[2] * outputShape[0],\n            boxRaw[3] * outputShape[1],\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n      // rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2] - h.box[0], h.box[3] - h.box[1]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n", "let instance = 0;\nlet CSScreated = false;\n\nlet theme = {\n  background: 'darkslategray',\n  hover: 'lightgray',\n  itemBackground: 'black',\n  itemColor: 'white',\n  buttonBackground: 'lightblue',\n  buttonHover: 'lightgreen',\n  checkboxOn: 'lightgreen',\n  checkboxOff: 'lightcoral',\n  rangeBackground: 'lightblue',\n  rangeLabel: 'white',\n  chartColor: 'lightblue',\n};\n\nfunction createCSS() {\n  if (CSScreated) return;\n  const css = `\n  :root { --rounded: 0.1rem; }\n  .menu { position: absolute; top: 0rem; right: 0; width: max-content; padding: 0 0.2rem 0 0.2rem; line-height: 1.8rem; z-index: 10;\n          box-shadow: 0 0 8px dimgrey; background: ${theme.background}; border-radius: var(--rounded); border-color: black; border-style: solid; border-width: thin; }\n\n  .menu:hover { box-shadow: 0 0 8px ${theme.hover}; }\n  .menu-container { display: block; max-height: 100vh; }\n  .menu-container-fadeout { max-height: 0; overflow: hidden; transition: max-height, 0.5s ease; }\n  .menu-container-fadein { max-height: 100vh; overflow: hidden; transition: max-height, 0.5s ease; }\n  .menu-item { display: flex; white-space: nowrap; padding: 0.2rem; cursor: default; width: 100%; }\n  .menu-title { cursor: pointer; }\n  .menu-hr { margin: 0.2rem; border: 1px solid rgba(0, 0, 0, 0.5) }\n  .menu-label { padding: 0; font-weight: 800; }\n\n  .menu-list { margin-right: 0.8rem; }\n  select:focus { outline: none; }\n  .menu-list-item { background: ${theme.itemBackground}; color: ${theme.itemColor}; border: none; padding: 0.2rem; font-family: inherit;\n    font-variant: inherit; border-radius: var(--rounded); font-weight: 800; }\n\n  .menu-chart-title { padding: 0; font-size: 0.8rem; font-weight: 800; align-items: center}\n  .menu-chart-canvas { background: transparent; margin: 0.2rem 0 0.2rem 0.6rem; }\n  \n  .menu-button { border: 0; background: ${theme.buttonBackground}; width: -webkit-fill-available; padding: 8px; margin: 8px; cursor: pointer; box-shadow: 4px 4px 4px 0 dimgrey;\n    border-radius: var(--rounded); justify-content: center; font-family: inherit; font-variant: inherit; font-size: 1rem; font-weight: 800; }\n  .menu-button:hover { background: ${theme.buttonHover}; box-shadow: 4px 4px 4px 0 black; }\n  .menu-button:focus { outline: none; }\n\n  .menu-checkbox { width: 2.8rem; height: 1rem; background: ${theme.itemBackground}; margin: 0.5rem 0.5rem 0 0; position: relative; border-radius: var(--rounded); }\n  .menu-checkbox:after { content: 'OFF'; color: ${theme.checkboxOff}; position: absolute; right: 0.2rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }\n  .menu-checkbox:before { content: 'ON'; color: ${theme.checkboxOn}; position: absolute; left: 0.3rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }\n  .menu-checkbox-label { width: 1.3rem; height: 0.8rem; cursor: pointer; position: absolute; top: 0.1rem; left: 0.1rem; z-index: 1; background: ${theme.checkboxOff};\n    border-radius: var(--rounded); transition: left 0.6s ease; }\n\n  input[type=checkbox] { visibility: hidden; }\n  input[type=checkbox]:checked + label { left: 1.4rem; background: ${theme.checkboxOn}; }\n\n  .menu-range { margin: 0.2rem 0.5rem 0 0; width: 3.5rem; background: transparent; color: ${theme.rangeBackground}; }\n  .menu-range:before { color: ${theme.rangeLabel}; margin: 0 0.4rem 0 0; font-weight: 800; font-size: 0.6rem; position: relative; top: 0.3rem; content: attr(value); }\n\n  input[type=range] { -webkit-appearance: none; }\n  input[type=range]::-webkit-slider-runnable-track { width: 100%; height: 1rem; cursor: pointer; background: ${theme.itemBackground}; border-radius: var(--rounded); border: 1px; }\n  input[type=range]::-moz-range-track { width: 100%; height: 1rem; cursor: pointer; background: ${theme.itemBackground}; border-radius: var(--rounded); border: 1px; }\n  input[type=range]::-webkit-slider-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${theme.rangeBackground}; cursor: pointer; -webkit-appearance: none; }\n  input[type=range]::-moz-range-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${theme.rangeBackground}; cursor: pointer; -webkit-appearance: none; }\n\n  .svg-background { fill:darkslategrey; cursor:pointer; opacity: 0.6; }\n  .svg-foreground { fill:white; cursor:pointer; opacity: 0.8; }\n  `;\n  const el = document.createElement('style');\n  el.innerHTML = css;\n  document.getElementsByTagName('head')[0].appendChild(el);\n  CSScreated = true;\n}\n\nclass Menu {\n  constructor(parent, title, position, userTheme) {\n    if (userTheme) theme = { ...theme, ...userTheme };\n    createCSS();\n    this.createMenu(parent, title, position);\n    this.id = 0;\n    this.instance = instance;\n    instance++;\n    this._maxFPS = 0;\n    this.hidden = 0;\n  }\n\n  createMenu(parent, title = '', position = { top: null, left: null, bottom: null, right: null }) {\n    this.menu = document.createElement('div');\n    this.menu.id = `menu-${instance}`;\n    this.menu.className = 'menu';\n    if (position) {\n      if (position.top) this.menu.style.top = position.top;\n      if (position.bottom) this.menu.style.bottom = position.bottom;\n      if (position.left) this.menu.style.left = position.left;\n      if (position.right) this.menu.style.right = position.right;\n    }\n\n    this.container = document.createElement('div');\n    this.container.id = `menu-container-${instance}`;\n    this.container.className = 'menu-container menu-container-fadein';\n\n    // set menu title with pulldown arrow\n    const elTitle = document.createElement('div');\n    elTitle.className = 'menu-title';\n    elTitle.id = `menu-title-${instance}`;\n    const svg = `<svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 448 512\" style=\"width: 2rem; height: 2rem; vertical-align: top;\">\n        <path d=\"M400 32H48A48 48 0 0 0 0 80v352a48 48 0 0 0 48 48h352a48 48 0 0 0 48-48V80a48 48 0 0 0-48-48zm-51.37 182.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z\" class=\"svg-background\"/>\n        <path d=\"M348.63 214.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z\" class=\"svg-foreground\"/>\n      </svg>`;\n    if (title) elTitle.innerHTML = `${title}${svg}`;\n    this.menu.appendChild(elTitle);\n    elTitle.addEventListener('click', () => {\n      this.container.classList.toggle('menu-container-fadeout');\n      this.container.classList.toggle('menu-container-fadein');\n      this.menu.style.borderStyle = this.container.classList.contains('menu-container-fadeout') ? 'none' : 'solid';\n    });\n\n    this.menu.appendChild(this.container);\n    if (typeof parent === 'object') parent.appendChild(this.menu);\n    else document.getElementById(parent).appendChild(this.menu);\n  }\n\n  get newID() {\n    this.id++;\n    return `menu-${this.instance}-${this.id}`;\n  }\n\n  get ID() {\n    return `menu-${this.instance}-${this.id}`;\n  }\n\n  get width() {\n    return this.menu.offsetWidth;\n  }\n\n  get height() {\n    return this.menu.offsetHeight;\n  }\n\n  hide() {\n    if (this.container.classList.contains('menu-container-fadein')) {\n      this.container.classList.toggle('menu-container-fadeout');\n      this.container.classList.toggle('menu-container-fadein');\n    }\n  }\n\n  visible() {\n    return (this.container.classList.contains('menu-container-fadein'));\n  }\n\n  toggle(evt) {\n    this.container.classList.toggle('menu-container-fadeout');\n    this.container.classList.toggle('menu-container-fadein');\n    if (this.container.classList.contains('menu-container-fadein') && evt) {\n      const x = evt.x || (evt.touches && evt.touches[0] ? evt.touches[0].pageX : null);\n      // const y = evt.y || (evt.touches && evt.touches[0] ? evt.touches[0].pageY : null);\n      if (x) this.menu.style.left = `${x - (this.menu.offsetWidth / 2)}px`;\n      // if (y) this.menu.style.top = '5.5rem'; // `${evt.y + 55}px`;\n      if (this.menu.offsetLeft < 0) this.menu.style.left = 0;\n      if ((this.menu.offsetLeft + this.menu.offsetWidth) > window.innerWidth) {\n        this.menu.style.left = null;\n        this.menu.style.right = 0;\n      }\n      this.menu.style.borderStyle = 'solid';\n    } else {\n      this.menu.style.borderStyle = 'none';\n    }\n  }\n\n  addTitle(title) {\n    const el = document.createElement('div');\n    el.className = 'menu-title';\n    el.id = this.newID;\n    el.innerHTML = title;\n    this.menu.appendChild(el);\n    el.addEventListener('click', () => {\n      this.hidden = !this.hidden;\n      const all = document.getElementsByClassName('menu');\n      for (const item of all) {\n        item.style.display = this.hidden ? 'none' : 'block';\n      }\n    });\n    return el;\n  }\n\n  addLabel(title) {\n    const el = document.createElement('div');\n    el.className = 'menu-item menu-label';\n    el.id = this.newID;\n    el.innerHTML = title;\n    this.container.appendChild(el);\n    return el;\n  }\n\n  addBool(title, object, variable, callback) {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    el.innerHTML = `<div class=\"menu-checkbox\"><input class=\"menu-checkbox\" type=\"checkbox\" id=\"${this.newID}\" ${object[variable] ? 'checked' : ''}/><label class=\"menu-checkbox-label\" for=\"${this.ID}\"></label></div>${title}`;\n    this.container.appendChild(el);\n    el.addEventListener('change', (evt) => {\n      object[variable] = evt.target.checked;\n      if (callback) callback(evt.target.checked);\n    });\n    return el;\n  }\n\n  async addList(title, items, selected, callback) {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    let options = '';\n    for (const item of items) {\n      const def = item === selected ? 'selected' : '';\n      options += `<option value=\"${item}\" ${def}>${item}</option>`;\n    }\n    el.innerHTML = `<div class=\"menu-list\"><select name=\"${this.ID}\" class=\"menu-list-item\">${options}</select><label for=\"${this.ID}\"></label></div>${title}`;\n    el.style.fontFamily = document.body.style.fontFamily;\n    el.style.fontSize = document.body.style.fontSize;\n    el.style.fontVariant = document.body.style.fontVariant;\n    this.container.appendChild(el);\n    el.addEventListener('change', (evt) => {\n      if (callback) callback(items[evt.target.selectedIndex]);\n    });\n    return el;\n  }\n\n  addRange(title, object, variable, min, max, step, callback) {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    el.innerHTML = `<input class=\"menu-range\" type=\"range\" id=\"${this.newID}\" min=\"${min}\" max=\"${max}\" step=\"${step}\" value=\"${object[variable]}\">${title}`;\n    this.container.appendChild(el);\n    el.addEventListener('change', (evt) => {\n      object[variable] = parseInt(evt.target.value) === parseFloat(evt.target.value) ? parseInt(evt.target.value) : parseFloat(evt.target.value);\n      evt.target.setAttribute('value', evt.target.value);\n      if (callback) callback(evt.target.value);\n    });\n    el.input = el.children[0];\n    return el;\n  }\n\n  addHTML(html) {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    el.id = this.newID;\n    if (html) el.innerHTML = html;\n    this.container.appendChild(el);\n    return el;\n  }\n\n  addButton(titleOn, titleOff, callback) {\n    const el = document.createElement('button');\n    el.className = 'menu-item menu-button';\n    el.style.fontFamily = document.body.style.fontFamily;\n    el.style.fontSize = document.body.style.fontSize;\n    el.style.fontVariant = document.body.style.fontVariant;\n    el.type = 'button';\n    el.id = this.newID;\n    el.innerText = titleOn;\n    this.container.appendChild(el);\n    el.addEventListener('click', () => {\n      if (el.innerText === titleOn) el.innerText = titleOff;\n      else el.innerText = titleOn;\n      if (callback) callback(el.innerText !== titleOn);\n    });\n    return el;\n  }\n\n  addValue(title, val, suffix = '') {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    el.id = `menu-val-${title}`;\n    el.innerText = `${title}: ${val}${suffix}`;\n    this.container.appendChild(el);\n    return el;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  updateValue(title, val, suffix = '') {\n    const el = document.getElementById(`menu-val-${title}`);\n    if (el) el.innerText = `${title}: ${val}${suffix}`;\n    else this.addValue(title, val);\n  }\n\n  addChart(title, id, width = 150, height = 40, color) {\n    if (color) theme.chartColor = color;\n    const el = document.createElement('div');\n    el.className = 'menu-item menu-chart-title';\n    el.id = this.newID;\n    el.innerHTML = `<font color=${theme.chartColor}>${title}</font><canvas id=\"menu-canvas-${id}\" class=\"menu-chart-canvas\" width=\"${width}px\" height=\"${height}px\"></canvas>`;\n    this.container.appendChild(el);\n    return el;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  async updateChart(id, values) {\n    if (!values || (values.length === 0)) return;\n    const canvas = document.getElementById(`menu-canvas-${id}`);\n    if (!canvas) return;\n    const ctx = canvas.getContext('2d');\n    ctx.fillStyle = theme.background;\n    ctx.fillRect(0, 0, canvas.width, canvas.height);\n    const width = canvas.width / values.length;\n    const max = 1 + Math.max(...values);\n    const height = canvas.height / max;\n    for (let i = 0; i < values.length; i++) {\n      const gradient = ctx.createLinearGradient(0, (max - values[i]) * height, 0, 0);\n      gradient.addColorStop(0.1, theme.chartColor);\n      gradient.addColorStop(0.4, theme.background);\n      ctx.fillStyle = gradient;\n      ctx.fillRect(i * width, 0, width - 4, canvas.height);\n      ctx.fillStyle = theme.background;\n      ctx.font = `${width / 1.5}px \"Segoe UI\"`;\n      ctx.fillText(Math.round(values[i]), i * width + 1, canvas.height - 1, width - 1);\n    }\n  }\n}\n\nexport default Menu;\n", "/* eslint-disable max-len */\n\n// based on: https://github.com/munrocket/gl-bench\n\nconst UICSS = `\n  #gl-bench { position: absolute; right: 1rem; bottom: 1rem; z-index:1000; -webkit-user-select: none; -moz-user-select: none; user-select: none; }\n  #gl-bench div { position: relative; display: block; margin: 4px; padding: 0 2px 0 2px; background: darkslategray; border-radius: 0.1rem; cursor: pointer; opacity: 0.9; }\n  #gl-bench svg { height: 60px; margin: 0 0px 0px 4px; }\n  #gl-bench text { font-size: 16px; font-family: 'Lato', 'Segoe UI'; dominant-baseline: middle; text-anchor: middle; }\n  #gl-bench .gl-mem { font-size: 12px; fill: white; }\n  #gl-bench .gl-fps { font-size: 13px; fill: white; }\n  #gl-bench line { stroke-width: 5; stroke: white; stroke-linecap: round; }\n  #gl-bench polyline { fill: none; stroke: white; stroke-linecap: round; stroke-linejoin: round; stroke-width: 3.5; }\n  #gl-bench rect { fill: black; }\n  #gl-bench .opacity { stroke: black; }\n  `;\n\nconst UISVG = `\n  <div class=\"gl-box\">\n    <svg viewBox=\"0 0 60 60\">\n      <text x=\"27\" y=\"56\" class=\"gl-fps\">00 FPS</text>\n      <text x=\"30\" y=\"8\" class=\"gl-mem\"></text>\n      <rect x=\"0\" y=\"14\" rx=\"4\" ry=\"4\" width=\"60\" height=\"32\"></rect>\n      <polyline class=\"gl-chart\"></polyline>\n    </svg>\n    <svg viewBox=\"0 0 14 60\" class=\"gl-cpu-svg\">\n      <line x1=\"7\" y1=\"38\" x2=\"7\" y2=\"11\" class=\"opacity\"/>\n      <line x1=\"7\" y1=\"38\" x2=\"7\" y2=\"11\" class=\"gl-cpu\" stroke-dasharray=\"0 27\"/>\n      <path d=\"M5.35 43c-.464 0-.812.377-.812.812v1.16c-.783.1972-1.421.812-1.595 1.624h-1.16c-.435 0-.812.348-.812.812s.348.812.812.812h1.102v1.653H1.812c-.464 0-.812.377-.812.812 0 .464.377.812.812.812h1.131c.1943.783.812 1.392 1.595 1.595v1.131c0 .464.377.812.812.812.464 0 .812-.377.812-.812V53.15h1.653v1.073c0 .464.377.812.812.812.464 0 .812-.377.812-.812v-1.131c.783-.1943 1.392-.812 1.595-1.595h1.131c.464 0 .812-.377.812-.812 0-.464-.377-.812-.812-.812h-1.073V48.22h1.102c.435 0 .812-.348.812-.812s-.348-.812-.812-.812h-1.16c-.1885-.783-.812-1.421-1.595-1.624v-1.131c0-.464-.377-.812-.812-.812-.464 0-.812.377-.812.812v1.073H6.162v-1.073c0-.464-.377-.812-.812-.812zm.58 3.48h2.088c.754 0 1.363.609 1.363 1.363v2.088c0 .754-.609 1.363-1.363 1.363H5.93c-.754 0-1.363-.609-1.363-1.363v-2.088c0-.754.609-1.363 1.363-1.363z\" style=\"fill: grey\"></path>\n    </svg>\n    <svg viewBox=\"0 0 14 60\" class=\"gl-gpu-svg\">\n      <line x1=\"7\" y1=\"38\" x2=\"7\" y2=\"11\" class=\"opacity\"/>\n      <line x1=\"7\" y1=\"38\" x2=\"7\" y2=\"11\" class=\"gl-gpu\" stroke-dasharray=\"0 27\"/>\n      <path d=\"M1.94775 43.3772a.736.736 0 10-.00416 1.472c.58535.00231.56465.1288.6348.3197.07015.18975.04933.43585.04933.43585l-.00653.05405v8.671a.736.736 0 101.472 0v-1.4145c.253.09522.52785.1495.81765.1495h5.267c1.2535 0 2.254-.9752 2.254-2.185v-3.105c0-1.2075-1.00625-2.185-2.254-2.185h-5.267c-.28865 0-.5635.05405-.8165.1495.01806-.16445.04209-.598-.1357-1.0787-.22425-.6072-.9499-1.2765-2.0125-1.2765zm2.9095 3.6455c.42435 0 .7659.36225.7659.8119v2.9785c0 .44965-.34155.8119-.7659.8119s-.7659-.36225-.7659-.8119v-2.9785c0-.44965.34155-.8119.7659-.8119zm4.117 0a2.3 2.3 0 012.3 2.3 2.3 2.3 0 01-2.3 2.3 2.3 2.3 0 01-2.3-2.3 2.3 2.3 0 012.3-2.3z\" style=\"fill: grey\"></path>\n    </svg>\n  </div>\n  `;\n\nclass GLBench {\n  /** GLBench constructor\n   * @param { WebGLRenderingContext | WebGL2RenderingContext } gl context\n   * @param { Object | undefined } settings additional settings\n   */\n  constructor(gl, settings = {}) {\n    this.css = UICSS;\n    this.svg = UISVG;\n    // eslint-disable-next-line @typescript-eslint/no-empty-function\n    this.paramLogger = () => {};\n    // eslint-disable-next-line @typescript-eslint/no-empty-function\n    this.chartLogger = () => {};\n    this.chartLen = 20;\n    this.chartHz = 20;\n\n    this.names = [];\n    this.cpuAccums = [];\n    this.gpuAccums = [];\n    this.activeAccums = [];\n    this.chart = new Array(this.chartLen);\n    this.now = () => ((performance && performance.now) ? performance.now() : Date.now());\n    this.updateUI = () => {\n      [].forEach.call(this.nodes['gl-gpu-svg'], (node) => node.style.display = this.trackGPU ? 'inline' : 'none');\n    };\n\n    Object.assign(this, settings);\n    this.detected = 0;\n    this.finished = [];\n    this.isFramebuffer = 0;\n    this.frameId = 0;\n\n    // 120hz device detection\n    let rafId; let n = 0; let\n      t0;\n    const loop = (t) => {\n      if (++n < 20) {\n        rafId = requestAnimationFrame(loop);\n      } else {\n        this.detected = Math.ceil(1e3 * n / (t - t0) / 70);\n        cancelAnimationFrame(rafId);\n      }\n      if (!t0) t0 = t;\n    };\n    requestAnimationFrame(loop);\n\n    // attach gpu profilers\n    if (gl) {\n      const glFinish = async (t, activeAccums) => Promise.resolve(setTimeout(() => {\n        gl.getError();\n        const dt = this.now() - t;\n        activeAccums.forEach((active, i) => {\n          if (active) this.gpuAccums[i] += dt;\n        });\n      }, 0));\n\n      const addProfiler = (fn, self, target) => {\n        const t = self.now();\n        // eslint-disable-next-line prefer-rest-params\n        fn.apply(target, arguments);\n        if (self.trackGPU) self.finished.push(glFinish(t, self.activeAccums.slice(0)));\n      };\n\n      /* ['drawArrays', 'drawElements', 'drawArraysInstanced', 'drawBuffers', 'drawElementsInstanced', 'drawRangeElements'].forEach((fn) => {\n        if (gl[fn]) {\n          gl[fn] = addProfiler(gl[fn], this, gl);\n        }\n      });\n      */\n      const fn = 'drawElements';\n      if (gl[fn]) {\n        gl[fn] = addProfiler(gl[fn], this, gl);\n      } else {\n        // eslint-disable-next-line no-console\n        console.log('bench: cannot attach to webgl function');\n      }\n\n      /*\n      gl.getExtension = ((fn, self) => {\n        // eslint-disable-next-line prefer-rest-params\n        const ext = fn.apply(gl, arguments);\n        if (ext) {\n          ['drawElementsInstancedANGLE', 'drawBuffersWEBGL'].forEach((fn2) => {\n            if (ext[fn2]) {\n              ext[fn2] = addProfiler(ext[fn2], self, ext);\n            }\n          });\n        }\n        return ext;\n      })(gl.getExtension, this);\n      */\n    }\n\n    // init ui and ui loggers\n    if (!this.withoutUI) {\n      if (!this.dom) this.dom = document.body;\n      const elm = document.createElement('div');\n      elm.id = 'gl-bench';\n      this.dom.appendChild(elm);\n      this.dom.insertAdjacentHTML('afterbegin', '<style id=\"gl-bench-style\">' + this.css + '</style>');\n      this.dom = elm;\n      this.dom.addEventListener('click', () => {\n        this.trackGPU = !this.trackGPU;\n        this.updateUI();\n      });\n\n      this.paramLogger = ((logger, dom, names) => {\n        const classes = ['gl-cpu', 'gl-gpu', 'gl-mem', 'gl-fps', 'gl-gpu-svg', 'gl-chart'];\n        const nodes = { ...classes };\n        classes.forEach((c) => nodes[c] = dom.getElementsByClassName(c));\n        this.nodes = nodes;\n        return (i, cpu, gpu, mem, fps, totalTime, frameId) => {\n          nodes['gl-cpu'][i].style.strokeDasharray = (cpu * 0.27).toFixed(0) + ' 100';\n          nodes['gl-gpu'][i].style.strokeDasharray = (gpu * 0.27).toFixed(0) + ' 100';\n          // eslint-disable-next-line no-nested-ternary\n          nodes['gl-mem'][i].innerHTML = names[i] ? names[i] : (mem ? 'mem: ' + mem.toFixed(0) + 'mb' : '');\n          nodes['gl-fps'][i].innerHTML = 'FPS: ' + fps.toFixed(1);\n          logger(names[i], cpu, gpu, mem, fps, totalTime, frameId);\n        };\n      })(this.paramLogger, this.dom, this.names);\n\n      this.chartLogger = ((logger, dom) => {\n        const nodes = { 'gl-chart': dom.getElementsByClassName('gl-chart') };\n        return (i, chart, circularId) => {\n          let points = '';\n          const len = chart.length;\n          for (let j = 0; j < len; j++) {\n            const id = (circularId + j + 1) % len;\n            if (chart[id] !== undefined) points = points + ' ' + (60 * j / (len - 1)).toFixed(1) + ',' + (45 - chart[id] * 0.5 / this.detected).toFixed(1);\n          }\n          nodes['gl-chart'][i].setAttribute('points', points);\n          logger(this.names[i], chart, circularId);\n        };\n      })(this.chartLogger, this.dom);\n    }\n  }\n\n  /**\n   * Explicit UI add\n   * @param { string | undefined } name\n   */\n  addUI(name) {\n    if (this.names.indexOf(name) === -1) {\n      this.names.push(name);\n      if (this.dom) {\n        this.dom.insertAdjacentHTML('beforeend', this.svg);\n        this.updateUI();\n      }\n      this.cpuAccums.push(0);\n      this.gpuAccums.push(0);\n      this.activeAccums.push(false);\n    }\n  }\n\n  /**\n   * Increase frameID\n   * @param { number | undefined } now\n   */\n  nextFrame(now) {\n    this.frameId++;\n    const t = now || this.now();\n\n    // params\n    if (this.frameId <= 1) {\n      this.paramFrame = this.frameId;\n      this.paramTime = t;\n    } else {\n      const duration = t - this.paramTime;\n      if (duration >= 1e3) {\n        const frameCount = this.frameId - this.paramFrame;\n        const fps = frameCount / duration * 1e3;\n        for (let i = 0; i < this.names.length; i++) {\n          const cpu = this.cpuAccums[i] / duration * 100;\n          const gpu = this.gpuAccums[i] / duration * 100;\n          const mem = (performance && performance.memory) ? performance.memory.usedJSHeapSize / (1 << 20) : 0;\n          this.paramLogger(i, cpu, gpu, mem, fps, duration, frameCount);\n          this.cpuAccums[i] = 0;\n          Promise.all(this.finished).then(() => {\n            this.gpuAccums[i] = 0;\n            this.finished = [];\n          });\n        }\n        this.paramFrame = this.frameId;\n        this.paramTime = t;\n      }\n    }\n\n    // chart\n    if (!this.detected || !this.chartFrame) {\n      this.chartFrame = this.frameId;\n      this.chartTime = t;\n      this.circularId = 0;\n    } else {\n      const timespan = t - this.chartTime;\n      let hz = this.chartHz * timespan / 1e3;\n      while (--hz > 0 && this.detected) {\n        const frameCount = this.frameId - this.chartFrame;\n        const fps = frameCount / timespan * 1e3;\n        this.chart[this.circularId % this.chartLen] = fps;\n        for (let i = 0; i < this.names.length; i++) this.chartLogger(i, this.chart, this.circularId);\n        this.circularId++;\n        this.chartFrame = this.frameId;\n        this.chartTime = t;\n      }\n    }\n  }\n\n  /**\n   * Begin named measurement\n   * @param { string | undefined } name\n   */\n  begin(name) {\n    this.updateAccums(name);\n  }\n\n  /**\n   * End named measure\n   * @param { string | undefined } name\n   */\n  end(name) {\n    this.updateAccums(name);\n  }\n\n  updateAccums(name) {\n    let nameId = this.names.indexOf(name);\n    if (nameId === -1) {\n      nameId = this.names.length;\n      this.addUI(name);\n    }\n\n    const t = this.now();\n    const dt = t - this.t0;\n    for (let i = 0; i < nameId + 1; i++) {\n      if (this.activeAccums[i]) this.cpuAccums[i] += dt;\n    }\n    this.activeAccums[nameId] = !this.activeAccums[nameId];\n    this.t0 = t;\n  }\n}\n\nexport default GLBench;\n", "// import Human from '../dist/human.esm.js'; // equivalent of @vladmandic/human\nimport Human from '../src/human';\nimport Menu from './menu.js';\nimport GLBench from './gl-bench.js';\n\nconst userConfig = { backend: 'webgl' }; // add any user configuration overrides\n\n/*\nconst userConfig = {\n  backend: 'wasm',\n  async: false,\n  warmup: 'full',\n  videoOptimized: true,\n  filter: { enabled: true },\n  face: { enabled: true, mesh: { enabled: true }, iris: { enabled: false }, age: { enabled: false }, gender: { enabled: false }, emotion: { enabled: false }, embedding: { enabled: false } },\n  hand: { enabled: false },\n  gesture: { enabled: false },\n  body: { enabled: false, modelPath: '../models/blazepose.json' },\n  object: { enabled: false },\n};\n*/\n\nconst human = new Human(userConfig);\n\n// ui options\nconst ui = {\n  baseBackground: 'rgba(50, 50, 50, 1)', // 'grey'\n  crop: true, // video mode crop to size or leave full frame\n  columns: 2, // when processing sample images create this many columns\n  facing: true, // camera facing front or back\n  useWorker: false, // use web workers for processing\n  worker: 'worker.js',\n  samples: ['../assets/sample6.jpg', '../assets/sample1.jpg', '../assets/sample4.jpg', '../assets/sample5.jpg', '../assets/sample3.jpg', '../assets/sample2.jpg'],\n  compare: '../assets/sample-me.jpg',\n  console: true, // log messages to browser console\n  maxFPSframes: 10, // keep fps history for how many frames\n  modelsPreload: true, // preload human models on startup\n  busy: false, // internal camera busy flag\n  menuWidth: 0, // internal\n  menuHeight: 0, // internal\n  camera: {}, // internal, holds details of webcam details\n  detectFPS: [], // internal, holds fps values for detection performance\n  drawFPS: [], // internal, holds fps values for draw performance\n  buffered: false, // experimental, should output be buffered between frames\n  drawWarmup: false, // debug only, should warmup image processing be displayed on startup\n  drawThread: null, // internl, perform draw operations in a separate thread\n  detectThread: null, // internl, perform detect operations in a separate thread\n  framesDraw: 0, // internal, statistics on frames drawn\n  framesDetect: 0, // internal, statistics on frames detected\n  bench: true, // show gl fps benchmark window\n  lastFrame: 0, // time of last frame processing\n};\n\n// global variables\nconst menu = {};\nlet worker;\nlet bench;\nlet lastDetectedResult = {};\n\n// helper function: translates json to human readable string\nfunction str(...msg) {\n  if (!Array.isArray(msg)) return msg;\n  let line = '';\n  for (const entry of msg) {\n    if (typeof entry === 'object') line += JSON.stringify(entry).replace(/{|}|\"|\\[|\\]/g, '').replace(/,/g, ', ');\n    else line += entry;\n  }\n  return line;\n}\n\n// helper function: wrapper around console output\nfunction log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (ui.console) console.log(ts, ...msg);\n}\n\nfunction status(msg) {\n  // eslint-disable-next-line no-console\n  const div = document.getElementById('status');\n  if (div) div.innerText = msg;\n}\n\nlet original;\nasync function calcSimmilariry(result) {\n  document.getElementById('compare-container').style.display = human.config.face.embedding.enabled ? 'block' : 'none';\n  if (!human.config.face.embedding.enabled) return;\n  if (!(result?.face?.length > 0) || (result?.face[0]?.embedding?.length >= 64)) return;\n  if (!original) {\n    original = result;\n    if (result.face[0].tensor) {\n      const enhanced = human.enhance(result.face[0]);\n      if (enhanced) {\n        const c = document.getElementById('orig');\n        const squeeze = enhanced.squeeze();\n        human.tf.browser.toPixels(squeeze, c);\n        enhanced.dispose();\n        squeeze.dispose();\n      }\n    } else {\n      document.getElementById('compare-canvas').getContext('2d').drawImage(original.canvas, 0, 0, 200, 200);\n    }\n  }\n  const simmilarity = human.simmilarity(original?.face[0]?.embedding, result?.face[0]?.embedding);\n  document.getElementById('simmilarity').innerText = `simmilarity: ${Math.trunc(1000 * simmilarity) / 10}%`;\n}\n\n// draws processed results and starts processing of a next frame\nlet lastDraw = performance.now();\nasync function drawResults(input) {\n  const result = lastDetectedResult;\n  const canvas = document.getElementById('canvas');\n\n  // update draw fps data\n  ui.drawFPS.push(1000 / (performance.now() - lastDraw));\n  if (ui.drawFPS.length > ui.maxFPSframes) ui.drawFPS.shift();\n  lastDraw = performance.now();\n\n  // draw fps chart\n  await menu.process.updateChart('FPS', ui.detectFPS);\n\n  // get updated canvas\n  if (ui.buffered || !result.canvas) {\n    const image = await human.image(input);\n    result.canvas = image.canvas;\n    human.tf.dispose(image.tensor);\n  }\n\n  // draw image from video\n  const ctx = canvas.getContext('2d');\n  ctx.fillStyle = ui.baseBackground;\n  ctx.fillRect(0, 0, canvas.width, canvas.height);\n  if (result.canvas) {\n    if (result.canvas.width !== canvas.width) canvas.width = result.canvas.width;\n    if (result.canvas.height !== canvas.height) canvas.height = result.canvas.height;\n    ctx.drawImage(result.canvas, 0, 0, result.canvas.width, result.canvas.height, 0, 0, result.canvas.width, result.canvas.height);\n  } else {\n    ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);\n  }\n\n  // draw all results\n  human.draw.face(canvas, result.face);\n  human.draw.body(canvas, result.body);\n  human.draw.hand(canvas, result.hand);\n  human.draw.object(canvas, result.object);\n  human.draw.gesture(canvas, result.gesture);\n  await calcSimmilariry(result);\n\n  // update log\n  const engine = human.tf.engine();\n  const gpu = engine.backendInstance ? `gpu: ${(engine.backendInstance.numBytesInGPU ? engine.backendInstance.numBytesInGPU : 0).toLocaleString()} bytes` : '';\n  const memory = `system: ${engine.state.numBytes.toLocaleString()} bytes ${gpu} | tensors: ${engine.state.numTensors.toLocaleString()}`;\n  const processing = result.canvas ? `processing: ${result.canvas.width} x ${result.canvas.height}` : '';\n  const avgDetect = Math.trunc(10 * ui.detectFPS.reduce((a, b) => a + b, 0) / ui.detectFPS.length) / 10;\n  const avgDraw = Math.trunc(10 * ui.drawFPS.reduce((a, b) => a + b, 0) / ui.drawFPS.length) / 10;\n  const warning = (ui.detectFPS.length > 5) && (avgDetect < 5) ? '<font color=\"lightcoral\">warning: your performance is low: try switching to higher performance backend, lowering resolution or disabling some models</font>' : '';\n  document.getElementById('log').innerHTML = `\n    video: ${ui.camera.name} | facing: ${ui.camera.facing} | screen: ${window.innerWidth} x ${window.innerHeight} camera: ${ui.camera.width} x ${ui.camera.height} ${processing}<br>\n    backend: ${human.tf.getBackend()} | ${memory}<br>\n    performance: ${str(result.performance)}ms FPS process:${avgDetect} refresh:${avgDraw}<br>\n    ${warning}<br>\n  `;\n\n  ui.framesDraw++;\n  ui.lastFrame = performance.now();\n  // if buffered, immediate loop but limit frame rate although it's going to run slower as JS is singlethreaded\n  if (ui.buffered) {\n    ui.drawThread = requestAnimationFrame(() => drawResults(input, canvas));\n  } else if (!ui.buffered && ui.drawThread) {\n    log('stopping buffered refresh');\n    cancelAnimationFrame(ui.drawThread);\n    ui.drawThread = null;\n  }\n}\n\n// setup webcam\nasync function setupCamera() {\n  if (ui.busy) return null;\n  ui.busy = true;\n  const video = document.getElementById('video');\n  const canvas = document.getElementById('canvas');\n  const output = document.getElementById('log');\n  const live = video.srcObject ? ((video.srcObject.getVideoTracks()[0].readyState === 'live') && (video.readyState > 2) && (!video.paused)) : false;\n  let msg = '';\n  status('setting up camera');\n  // setup webcam. note that navigator.mediaDevices requires that page is accessed via https\n  if (!navigator.mediaDevices) {\n    msg = 'camera access not supported';\n    output.innerText += `\\n${msg}`;\n    log(msg);\n    status(msg);\n    ui.busy = false;\n    return msg;\n  }\n  let stream;\n  const constraints = {\n    audio: false,\n    video: { facingMode: ui.facing ? 'user' : 'environment', resizeMode: ui.crop ? 'crop-and-scale' : 'none' },\n  };\n  if (window.innerWidth > window.innerHeight) constraints.video.width = { ideal: window.innerWidth };\n  else constraints.video.height = { ideal: (window.innerHeight - document.getElementById('menubar').offsetHeight) };\n  try {\n    stream = await navigator.mediaDevices.getUserMedia(constraints);\n  } catch (err) {\n    if (err.name === 'PermissionDeniedError' || err.name === 'NotAllowedError') msg = 'camera permission denied';\n    else if (err.name === 'SourceUnavailableError') msg = 'camera not available';\n    else msg = `camera error: ${err.message || err}`;\n    output.innerText += `\\n${msg}`;\n    status(msg);\n    log('camera error:', err);\n    ui.busy = false;\n    return msg;\n  }\n  if (stream) video.srcObject = stream;\n  else {\n    ui.busy = false;\n    return 'camera stream empty';\n  }\n  const track = stream.getVideoTracks()[0];\n  const settings = track.getSettings();\n  // log('camera constraints:', constraints, 'window:', { width: window.innerWidth, height: window.innerHeight }, 'settings:', settings, 'track:', track);\n  ui.camera = { name: track.label?.toLowerCase(), width: settings.width, height: settings.height, facing: settings.facingMode === 'user' ? 'front' : 'back' };\n  return new Promise((resolve) => {\n    video.onloadeddata = async () => {\n      video.width = video.videoWidth;\n      video.height = video.videoHeight;\n      canvas.width = video.width;\n      canvas.height = video.height;\n      canvas.style.width = canvas.width > canvas.height ? '100vw' : '';\n      canvas.style.height = canvas.width > canvas.height ? '' : '100vh';\n      ui.menuWidth.input.setAttribute('value', video.width);\n      ui.menuHeight.input.setAttribute('value', video.height);\n      // silly font resizing for paint-on-canvas since viewport can be zoomed\n      if (live) video.play();\n      // eslint-disable-next-line no-use-before-define\n      if (live && !ui.detectThread) runHumanDetect(video, canvas);\n      ui.busy = false;\n      // do once more because onresize events can be delayed or skipped\n      // if (video.width > window.innerWidth) await setupCamera();\n      status('');\n      resolve();\n    };\n  });\n}\n\nfunction initPerfMonitor() {\n  if (!bench) {\n    const gl = null;\n    // cosnt gl = human.tf.engine().backend.gpgpu.gl;\n    // if (!gl) log('bench cannot get tensorflow webgl context');\n    bench = new GLBench(gl, {\n      trackGPU: false, // this is really slow\n      chartHz: 20,\n      chartLen: 20,\n    });\n    bench.begin();\n  }\n}\n\n// wrapper for worker.postmessage that creates worker if one does not exist\nfunction webWorker(input, image, canvas, timestamp) {\n  if (!worker) {\n    // create new webworker and add event handler only once\n    log('creating worker thread');\n    worker = new Worker(ui.worker, { type: 'module' });\n    // after receiving message from webworker, parse&draw results and send new frame for processing\n    worker.addEventListener('message', (msg) => {\n      if (msg.data.result.performance && msg.data.result.performance.total) ui.detectFPS.push(1000 / msg.data.result.performance.total);\n      if (ui.detectFPS.length > ui.maxFPSframes) ui.detectFPS.shift();\n      if (ui.bench) {\n        if (!bench) initPerfMonitor();\n        bench.nextFrame(timestamp);\n      }\n      if (document.getElementById('gl-bench')) document.getElementById('gl-bench').style.display = ui.bench ? 'block' : 'none';\n      lastDetectedResult = msg.data.result;\n      ui.framesDetect++;\n      if (!ui.drawThread) drawResults(input);\n      // eslint-disable-next-line no-use-before-define\n      ui.detectThread = requestAnimationFrame((now) => runHumanDetect(input, canvas, now));\n    });\n  }\n  // pass image data as arraybuffer to worker by reference to avoid copy\n  worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height, userConfig }, [image.data.buffer]);\n}\n\n// main processing function when input is webcam, can use direct invocation or web worker\nfunction runHumanDetect(input, canvas, timestamp) {\n  // if live video\n  const live = input.srcObject && (input.srcObject.getVideoTracks()[0].readyState === 'live') && (input.readyState > 2) && (!input.paused);\n  if (!live && input.srcObject) {\n    // stop ui refresh\n    if (ui.drawThread) cancelAnimationFrame(ui.drawThread);\n    if (ui.detectThread) cancelAnimationFrame(ui.detectThread);\n    ui.drawThread = null;\n    ui.detectThread = null;\n    // if we want to continue and camera not ready, retry in 0.5sec, else just give up\n    if (input.paused) log('camera paused');\n    else if ((input.srcObject.getVideoTracks()[0].readyState === 'live') && (input.readyState <= 2)) setTimeout(() => runHumanDetect(input, canvas), 500);\n    else log(`camera not ready: track state: ${input.srcObject?.getVideoTracks()[0].readyState} stream state: ${input.readyState}`);\n    clearTimeout(ui.drawThread);\n    ui.drawThread = null;\n    log('frame statistics: process:', ui.framesDetect, 'refresh:', ui.framesDraw);\n    log('memory', human.tf.engine().memory());\n    return;\n  }\n  status('');\n  if (ui.useWorker) {\n    // get image data from video as we cannot send html objects to webworker\n    const offscreen = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(canvas.width, canvas.height) : document.createElement('canvas');\n    offscreen.width = canvas.width;\n    offscreen.height = canvas.height;\n    const ctx = offscreen.getContext('2d');\n    ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);\n    const data = ctx.getImageData(0, 0, canvas.width, canvas.height);\n    // perform detection in worker\n    webWorker(input, data, canvas, userConfig, timestamp);\n  } else {\n    human.detect(input, userConfig).then((result) => {\n      if (result.performance && result.performance.total) ui.detectFPS.push(1000 / result.performance.total);\n      if (ui.detectFPS.length > ui.maxFPSframes) ui.detectFPS.shift();\n      if (ui.bench) {\n        if (!bench) initPerfMonitor();\n        bench.nextFrame(timestamp);\n      }\n      if (document.getElementById('gl-bench')) document.getElementById('gl-bench').style.display = ui.bench ? 'block' : 'none';\n      if (result.error) {\n        log(result.error);\n        document.getElementById('log').innerText += `\\nHuman error: ${result.error}`;\n      } else {\n        lastDetectedResult = result;\n        if (!ui.drawThread) drawResults(input);\n        ui.framesDetect++;\n        ui.detectThread = requestAnimationFrame((now) => runHumanDetect(input, canvas, now));\n      }\n    });\n  }\n}\n\n// main processing function when input is image, can use direct invocation or web worker\nasync function processImage(input) {\n  return new Promise((resolve) => {\n    const image = new Image();\n    image.onload = async () => {\n      log('Processing image:', encodeURI(image.src));\n      const canvas = document.getElementById('canvas');\n      image.width = image.naturalWidth;\n      image.height = image.naturalHeight;\n      canvas.width = human.config.filter.width && human.config.filter.width > 0 ? human.config.filter.width : image.naturalWidth;\n      canvas.height = human.config.filter.height && human.config.filter.height > 0 ? human.config.filter.height : image.naturalHeight;\n      const result = await human.detect(image, userConfig);\n      lastDetectedResult = result;\n      await drawResults(image);\n      const thumb = document.createElement('canvas');\n      thumb.className = 'thumbnail';\n      thumb.width = window.innerWidth / (ui.columns + 0.1);\n      thumb.height = thumb.width * canvas.height / canvas.width;\n      if (result.face && result.face.length > 0) {\n        thumb.title = result.face.map((a, i) => `#${i} face: ${Math.trunc(100 * a.faceConfidence)}% box: ${Math.trunc(100 * a.boxConfidence)}% age: ${Math.trunc(a.age)} gender: ${Math.trunc(100 * a.genderConfidence)}% ${a.gender}`).join(' | ');\n      } else {\n        thumb.title = 'no face detected';\n      }\n      const ctx = thumb.getContext('2d');\n      ctx.drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, thumb.width, thumb.height);\n      document.getElementById('samples-container').appendChild(thumb);\n      image.src = '';\n      resolve(true);\n    };\n    image.src = input;\n  });\n}\n\n// just initialize everything and call main function\nasync function detectVideo() {\n  document.getElementById('samples-container').style.display = 'none';\n  document.getElementById('canvas').style.display = 'block';\n  const video = document.getElementById('video');\n  const canvas = document.getElementById('canvas');\n  if ((video.srcObject !== null) && !video.paused) {\n    document.getElementById('play').style.display = 'block';\n    document.getElementById('btnStart').className = 'button button-start';\n    document.getElementById('btnStart').innerHTML = 'start<br>video';\n    status('paused');\n    video.pause();\n  } else {\n    const cameraError = await setupCamera();\n    if (!cameraError) {\n      document.getElementById('play').style.display = 'none';\n      for (const m of Object.values(menu)) m.hide();\n      status('');\n      document.getElementById('btnStart').className = 'button button-stop';\n      document.getElementById('btnStart').innerHTML = 'pause<br>video';\n      await video.play();\n      if (!ui.detectThread) runHumanDetect(video, canvas);\n    } else {\n      status(cameraError);\n    }\n  }\n}\n\n// just initialize everything and call main function\nasync function detectSampleImages() {\n  userConfig.videoOptimized = false; // force disable video optimizations\n  document.getElementById('play').style.display = 'none';\n  document.getElementById('canvas').style.display = 'none';\n  document.getElementById('samples-container').style.display = 'block';\n  log('Running detection of sample images');\n  status('processing images');\n  document.getElementById('samples-container').innerHTML = '';\n  for (const m of Object.values(menu)) m.hide();\n  for (const image of ui.samples) await processImage(image);\n  status('');\n}\n\nfunction setupMenu() {\n  let x = [];\n  if (window.innerWidth > 800) {\n    // initial position of menu items, later it's calculated based on mouse coordinates\n    x = [`${document.getElementById('btnDisplay').offsetLeft - 50}px`, `${document.getElementById('btnImage').offsetLeft - 50}px`, `${document.getElementById('btnProcess').offsetLeft - 50}px`, `${document.getElementById('btnModel').offsetLeft - 50}px`];\n  } else {\n    // absolute minimum spacing for menus\n    x = ['0rem', '11rem', '21.1rem', '33rem'];\n  }\n\n  menu.display = new Menu(document.body, '', { top: `${document.getElementById('menubar').offsetHeight}px`, left: x[0] });\n  menu.display.addBool('perf monitor', ui, 'bench', (val) => ui.bench = val);\n  menu.display.addBool('buffered output', ui, 'buffered', (val) => ui.buffered = val);\n  menu.display.addBool('crop & scale', ui, 'crop', (val) => {\n    ui.crop = val;\n    setupCamera();\n  });\n  menu.display.addBool('camera facing', ui, 'facing', (val) => {\n    ui.facing = val;\n    setupCamera();\n  });\n  menu.display.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.display.addBool('use 3D depth', human.draw.drawOptions, 'useDepth');\n  menu.display.addBool('draw with curves', human.draw.drawOptions, 'useCurves');\n  menu.display.addBool('print labels', human.draw.drawOptions, 'drawLabels');\n  menu.display.addBool('draw points', human.draw.drawOptions, 'drawPoints');\n  menu.display.addBool('draw boxes', human.draw.drawOptions, 'drawBoxes');\n  menu.display.addBool('draw polygons', human.draw.drawOptions, 'drawPolygons');\n  menu.display.addBool('fill polygons', human.draw.drawOptions, 'fillPolygons');\n\n  menu.image = new Menu(document.body, '', { top: `${document.getElementById('menubar').offsetHeight}px`, left: x[1] });\n  menu.image.addBool('enabled', human.config.filter, 'enabled', (val) => human.config.filter.enabled = val);\n  ui.menuWidth = menu.image.addRange('image width', human.config.filter, 'width', 0, 3840, 10, (val) => human.config.filter.width = parseInt(val));\n  ui.menuHeight = menu.image.addRange('image height', human.config.filter, 'height', 0, 2160, 10, (val) => human.config.filter.height = parseInt(val));\n  menu.image.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.image.addRange('brightness', human.config.filter, 'brightness', -1.0, 1.0, 0.05, (val) => human.config.filter.brightness = parseFloat(val));\n  menu.image.addRange('contrast', human.config.filter, 'contrast', -1.0, 1.0, 0.05, (val) => human.config.filter.contrast = parseFloat(val));\n  menu.image.addRange('sharpness', human.config.filter, 'sharpness', 0, 1.0, 0.05, (val) => human.config.filter.sharpness = parseFloat(val));\n  menu.image.addRange('blur', human.config.filter, 'blur', 0, 20, 1, (val) => human.config.filter.blur = parseInt(val));\n  menu.image.addRange('saturation', human.config.filter, 'saturation', -1.0, 1.0, 0.05, (val) => human.config.filter.saturation = parseFloat(val));\n  menu.image.addRange('hue', human.config.filter, 'hue', 0, 360, 5, (val) => human.config.filter.hue = parseInt(val));\n  menu.image.addRange('pixelate', human.config.filter, 'pixelate', 0, 32, 1, (val) => human.config.filter.pixelate = parseInt(val));\n  menu.image.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.image.addBool('negative', human.config.filter, 'negative', (val) => human.config.filter.negative = val);\n  menu.image.addBool('sepia', human.config.filter, 'sepia', (val) => human.config.filter.sepia = val);\n  menu.image.addBool('vintage', human.config.filter, 'vintage', (val) => human.config.filter.vintage = val);\n  menu.image.addBool('kodachrome', human.config.filter, 'kodachrome', (val) => human.config.filter.kodachrome = val);\n  menu.image.addBool('technicolor', human.config.filter, 'technicolor', (val) => human.config.filter.technicolor = val);\n  menu.image.addBool('polaroid', human.config.filter, 'polaroid', (val) => human.config.filter.polaroid = val);\n\n  menu.process = new Menu(document.body, '', { top: `${document.getElementById('menubar').offsetHeight}px`, left: x[2] });\n  menu.process.addList('backend', ['cpu', 'webgl', 'wasm', 'humangl'], human.config.backend, (val) => human.config.backend = val);\n  menu.process.addBool('async operations', human.config, 'async', (val) => human.config.async = val);\n  // menu.process.addBool('enable profiler', human.config, 'profile', (val) => human.config.profile = val);\n  // menu.process.addBool('memory shield', human.config, 'deallocate', (val) => human.config.deallocate = val);\n  menu.process.addBool('use web worker', ui, 'useWorker');\n  menu.process.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.process.addLabel('model parameters');\n  menu.process.addRange('max objects', human.config.face.detector, 'maxFaces', 1, 50, 1, (val) => {\n    human.config.face.detector.maxFaces = parseInt(val);\n    human.config.body.maxDetections = parseInt(val);\n    human.config.hand.maxHands = parseInt(val);\n  });\n  menu.process.addRange('skip frames', human.config.face.detector, 'skipFrames', 0, 50, 1, (val) => {\n    human.config.face.detector.skipFrames = parseInt(val);\n    human.config.face.emotion.skipFrames = parseInt(val);\n    human.config.face.age.skipFrames = parseInt(val);\n    human.config.hand.skipFrames = parseInt(val);\n  });\n  menu.process.addRange('min confidence', human.config.face.detector, 'minConfidence', 0.0, 1.0, 0.05, (val) => {\n    human.config.face.detector.minConfidence = parseFloat(val);\n    human.config.face.gender.minConfidence = parseFloat(val);\n    human.config.face.emotion.minConfidence = parseFloat(val);\n    human.config.hand.minConfidence = parseFloat(val);\n  });\n  menu.process.addRange('score threshold', human.config.face.detector, 'scoreThreshold', 0.1, 1.0, 0.05, (val) => {\n    human.config.face.detector.scoreThreshold = parseFloat(val);\n    human.config.hand.scoreThreshold = parseFloat(val);\n    human.config.body.scoreThreshold = parseFloat(val);\n  });\n  menu.process.addRange('overlap', human.config.face.detector, 'iouThreshold', 0.1, 1.0, 0.05, (val) => {\n    human.config.face.detector.iouThreshold = parseFloat(val);\n    human.config.hand.iouThreshold = parseFloat(val);\n  });\n  menu.process.addBool('detection rotation', human.config.face.detector, 'rotation', (val) => {\n    human.config.face.detector.rotation = val;\n    human.config.hand.rotation = val;\n  });\n  menu.process.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.process.addButton('process sample images', 'process images', () => detectSampleImages());\n  menu.process.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.process.addChart('FPS', 'FPS');\n\n  menu.models = new Menu(document.body, '', { top: `${document.getElementById('menubar').offsetHeight}px`, left: x[3] });\n  menu.models.addBool('face detect', human.config.face, 'enabled', (val) => human.config.face.enabled = val);\n  menu.models.addBool('face mesh', human.config.face.mesh, 'enabled', (val) => human.config.face.mesh.enabled = val);\n  menu.models.addBool('face iris', human.config.face.iris, 'enabled', (val) => human.config.face.iris.enabled = val);\n  menu.models.addBool('face age', human.config.face.age, 'enabled', (val) => human.config.face.age.enabled = val);\n  menu.models.addBool('face gender', human.config.face.gender, 'enabled', (val) => human.config.face.gender.enabled = val);\n  menu.models.addBool('face emotion', human.config.face.emotion, 'enabled', (val) => human.config.face.emotion.enabled = val);\n  menu.models.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.models.addBool('body pose', human.config.body, 'enabled', (val) => human.config.body.enabled = val);\n  menu.models.addBool('hand pose', human.config.hand, 'enabled', (val) => human.config.hand.enabled = val);\n  menu.models.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.models.addBool('gestures', human.config.gesture, 'enabled', (val) => human.config.gesture.enabled = val);\n  menu.models.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.models.addBool('object detection', human.config.object, 'enabled', (val) => human.config.object.enabled = val);\n  menu.models.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.models.addBool('face compare', human.config.face.embedding, 'enabled', (val) => {\n    human.config.face.embedding.enabled = val;\n    original = null;\n  });\n\n  document.getElementById('btnDisplay').addEventListener('click', (evt) => menu.display.toggle(evt));\n  document.getElementById('btnImage').addEventListener('click', (evt) => menu.image.toggle(evt));\n  document.getElementById('btnProcess').addEventListener('click', (evt) => menu.process.toggle(evt));\n  document.getElementById('btnModel').addEventListener('click', (evt) => menu.models.toggle(evt));\n  document.getElementById('btnStart').addEventListener('click', () => detectVideo());\n  document.getElementById('play').addEventListener('click', () => detectVideo());\n}\n\nasync function drawWarmup(res) {\n  const canvas = document.getElementById('canvas');\n  canvas.width = res.canvas.width;\n  canvas.height = res.canvas.height;\n  const ctx = canvas.getContext('2d');\n  ctx.drawImage(res.canvas, 0, 0, res.canvas.width, res.canvas.height, 0, 0, canvas.width, canvas.height);\n  await human.draw.all(canvas, res);\n}\n\nasync function main() {\n  log('Demo starting ...');\n  setupMenu();\n  document.getElementById('log').innerText = `Human: version ${human.version}`;\n  if (ui.modelsPreload && !ui.useWorker) {\n    status('loading');\n    await human.load(userConfig); // this is not required, just pre-loads all models\n    const loaded = Object.keys(human.models).filter((a) => human.models[a]);\n    log('Demo loaded models:', loaded);\n  }\n  if (!ui.useWorker) {\n    status('initializing');\n    const res = await human.warmup(userConfig); // this is not required, just pre-warms all models for faster initial inference\n    if (res && res.canvas && ui.drawWarmup) await drawWarmup(res);\n  }\n  status('human: ready');\n  document.getElementById('loader').style.display = 'none';\n  document.getElementById('play').style.display = 'block';\n  log('Demo ready...');\n}\n\nwindow.onload = main;\nwindow.onresize = setupCamera;\n"],
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"../src/gender/gender.ts", "../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/decodePose.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/box.ts", "../src/handpose/handdetector.ts", "../src/handpose/util.ts", "../src/handpose/handpipeline.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/nanodet/nanodet.ts", "../src/gesture/gesture.ts", "../src/imagefx.js", "../src/image.ts", "../config.ts", "../src/sample.ts", "../src/draw.ts", "../demo/menu.js", "../demo/gl-bench.js", "../demo/browser.js"],
+  "sourcesContent": ["import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 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Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw 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ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){err(\"requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];var contextAttributes={\"alpha\":!!GROWABLE_HEAP_I32()[a+(0>>2)],\"depth\":!!GROWABLE_HEAP_I32()[a+(4>>2)],\"stencil\":!!GROWABLE_HEAP_I32()[a+(8>>2)],\"antialias\":!!GROWABLE_HEAP_I32()[a+(12>>2)],\"premultipliedAlpha\":!!GROWABLE_HEAP_I32()[a+(16>>2)],\"preserveDrawingBuffer\":!!GROWABLE_HEAP_I32()[a+(20>>2)],\"powerPreference\":__emscripten_webgl_power_preferences[powerPreference],\"failIfMajorPerformanceCaveat\":!!GROWABLE_HEAP_I32()[a+(28>>2)],majorVersion:GROWABLE_HEAP_I32()[a+(32>>2)],minorVersion:GROWABLE_HEAP_I32()[a+(36>>2)],enableExtensionsByDefault:GROWABLE_HEAP_I32()[a+(40>>2)],explicitSwapControl:GROWABLE_HEAP_I32()[a+(44>>2)],proxyContextToMainThread:GROWABLE_HEAP_I32()[a+(48>>2)],renderViaOffscreenBackBuffer:GROWABLE_HEAP_I32()[a+(52>>2)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var 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cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,HEAPU8,outPtr,maxBytesToWrite)}function writeArrayToMemory(array,buffer){HEAP8.set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;__ATINIT__.push({func:function(){___wasm_call_ctors()}});function preRun(){if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=HEAP32[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){}function _fd_write(fd,iov,iovcnt,pnum){var num=0;for(var i=0;i<iovcnt;i++){var ptr=HEAP32[iov+i*8>>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j])}num+=len}HEAP32[pnum>>2]=num;return 0}var asmLibraryArg={\"a\":_abort,\"d\":_emscripten_memcpy_big,\"e\":_emscripten_resize_heap,\"f\":_fd_close,\"c\":_fd_seek,\"b\":_fd_write};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"h\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"i\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"j\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"k\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"l\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"n\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"o\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"p\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"q\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"r\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"s\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"t\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"u\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"v\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"w\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"x\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"y\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"z\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"F\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var 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_Rsqrt=Module[\"_Rsqrt\"]=function(){return(_Rsqrt=Module[\"_Rsqrt\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var _ScatterNd=Module[\"_ScatterNd\"]=function(){return(_ScatterNd=Module[\"_ScatterNd\"]=Module[\"asm\"][\"qa\"]).apply(null,arguments)};var _SelectV2=Module[\"_SelectV2\"]=function(){return(_SelectV2=Module[\"_SelectV2\"]=Module[\"asm\"][\"ra\"]).apply(null,arguments)};var _Sigmoid=Module[\"_Sigmoid\"]=function(){return(_Sigmoid=Module[\"_Sigmoid\"]=Module[\"asm\"][\"sa\"]).apply(null,arguments)};var _Sin=Module[\"_Sin\"]=function(){return(_Sin=Module[\"_Sin\"]=Module[\"asm\"][\"ta\"]).apply(null,arguments)};var _Softmax=Module[\"_Softmax\"]=function(){return(_Softmax=Module[\"_Softmax\"]=Module[\"asm\"][\"ua\"]).apply(null,arguments)};var _Sqrt=Module[\"_Sqrt\"]=function(){return(_Sqrt=Module[\"_Sqrt\"]=Module[\"asm\"][\"va\"]).apply(null,arguments)};var 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(e){try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 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0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    boxRaw: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.#perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: prediction.confidence, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            Math.max(0, (boxRaw[0] * outputShape[0])),\n            Math.max(0, (boxRaw[1] * outputShape[1])),\n            Math.min(1, (boxRaw[2] * outputShape[0]) - (boxRaw[0] * outputShape[0])),\n            Math.min(1, (boxRaw[3] * outputShape[1]) - (boxRaw[1] * outputShape[1])),\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n", "let instance = 0;\nlet CSScreated = false;\n\nlet theme = {\n  background: 'darkslategray',\n  hover: 'lightgray',\n  itemBackground: 'black',\n  itemColor: 'white',\n  buttonBackground: 'lightblue',\n  buttonHover: 'lightgreen',\n  checkboxOn: 'lightgreen',\n  checkboxOff: 'lightcoral',\n  rangeBackground: 'lightblue',\n  rangeLabel: 'white',\n  chartColor: 'lightblue',\n};\n\nfunction createCSS() {\n  if (CSScreated) return;\n  const css = `\n  :root { --rounded: 0.1rem; }\n  .menu { position: absolute; top: 0rem; right: 0; width: max-content; padding: 0 0.2rem 0 0.2rem; line-height: 1.8rem; z-index: 10;\n          box-shadow: 0 0 8px dimgrey; background: ${theme.background}; border-radius: var(--rounded); border-color: black; border-style: solid; border-width: thin; }\n\n  .menu:hover { box-shadow: 0 0 8px ${theme.hover}; }\n  .menu-container { display: block; max-height: 100vh; }\n  .menu-container-fadeout { max-height: 0; overflow: hidden; transition: max-height, 0.5s ease; }\n  .menu-container-fadein { max-height: 100vh; overflow: hidden; transition: max-height, 0.5s ease; }\n  .menu-item { display: flex; white-space: nowrap; padding: 0.2rem; cursor: default; width: 100%; }\n  .menu-title { cursor: pointer; }\n  .menu-hr { margin: 0.2rem; border: 1px solid rgba(0, 0, 0, 0.5) }\n  .menu-label { padding: 0; font-weight: 800; }\n\n  .menu-list { margin-right: 0.8rem; }\n  select:focus { outline: none; }\n  .menu-list-item { background: ${theme.itemBackground}; color: ${theme.itemColor}; border: none; padding: 0.2rem; font-family: inherit;\n    font-variant: inherit; border-radius: var(--rounded); font-weight: 800; }\n\n  .menu-chart-title { padding: 0; font-size: 0.8rem; font-weight: 800; align-items: center}\n  .menu-chart-canvas { background: transparent; margin: 0.2rem 0 0.2rem 0.6rem; }\n  \n  .menu-button { border: 0; background: ${theme.buttonBackground}; width: -webkit-fill-available; padding: 8px; margin: 8px; cursor: pointer; box-shadow: 4px 4px 4px 0 dimgrey;\n    border-radius: var(--rounded); justify-content: center; font-family: inherit; font-variant: inherit; font-size: 1rem; font-weight: 800; }\n  .menu-button:hover { background: ${theme.buttonHover}; box-shadow: 4px 4px 4px 0 black; }\n  .menu-button:focus { outline: none; }\n\n  .menu-checkbox { width: 2.8rem; height: 1rem; background: ${theme.itemBackground}; margin: 0.5rem 0.5rem 0 0; position: relative; border-radius: var(--rounded); }\n  .menu-checkbox:after { content: 'OFF'; color: ${theme.checkboxOff}; position: absolute; right: 0.2rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }\n  .menu-checkbox:before { content: 'ON'; color: ${theme.checkboxOn}; position: absolute; left: 0.3rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; }\n  .menu-checkbox-label { width: 1.3rem; height: 0.8rem; cursor: pointer; position: absolute; top: 0.1rem; left: 0.1rem; z-index: 1; background: ${theme.checkboxOff};\n    border-radius: var(--rounded); transition: left 0.6s ease; }\n\n  input[type=checkbox] { visibility: hidden; }\n  input[type=checkbox]:checked + label { left: 1.4rem; background: ${theme.checkboxOn}; }\n\n  .menu-range { margin: 0.2rem 0.5rem 0 0; width: 3.5rem; background: transparent; color: ${theme.rangeBackground}; }\n  .menu-range:before { color: ${theme.rangeLabel}; margin: 0 0.4rem 0 0; font-weight: 800; font-size: 0.6rem; position: relative; top: 0.3rem; content: attr(value); }\n\n  input[type=range] { -webkit-appearance: none; }\n  input[type=range]::-webkit-slider-runnable-track { width: 100%; height: 1rem; cursor: pointer; background: ${theme.itemBackground}; border-radius: var(--rounded); border: 1px; }\n  input[type=range]::-moz-range-track { width: 100%; height: 1rem; cursor: pointer; background: ${theme.itemBackground}; border-radius: var(--rounded); border: 1px; }\n  input[type=range]::-webkit-slider-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${theme.rangeBackground}; cursor: pointer; -webkit-appearance: none; }\n  input[type=range]::-moz-range-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${theme.rangeBackground}; cursor: pointer; -webkit-appearance: none; }\n\n  .svg-background { fill:darkslategrey; cursor:pointer; opacity: 0.6; }\n  .svg-foreground { fill:white; cursor:pointer; opacity: 0.8; }\n  `;\n  const el = document.createElement('style');\n  el.innerHTML = css;\n  document.getElementsByTagName('head')[0].appendChild(el);\n  CSScreated = true;\n}\n\nclass Menu {\n  constructor(parent, title, position, userTheme) {\n    if (userTheme) theme = { ...theme, ...userTheme };\n    createCSS();\n    this.createMenu(parent, title, position);\n    this.id = 0;\n    this.instance = instance;\n    instance++;\n    this._maxFPS = 0;\n    this.hidden = 0;\n  }\n\n  createMenu(parent, title = '', position = { top: null, left: null, bottom: null, right: null }) {\n    this.menu = document.createElement('div');\n    this.menu.id = `menu-${instance}`;\n    this.menu.className = 'menu';\n    if (position) {\n      if (position.top) this.menu.style.top = position.top;\n      if (position.bottom) this.menu.style.bottom = position.bottom;\n      if (position.left) this.menu.style.left = position.left;\n      if (position.right) this.menu.style.right = position.right;\n    }\n\n    this.container = document.createElement('div');\n    this.container.id = `menu-container-${instance}`;\n    this.container.className = 'menu-container menu-container-fadein';\n\n    // set menu title with pulldown arrow\n    const elTitle = document.createElement('div');\n    elTitle.className = 'menu-title';\n    elTitle.id = `menu-title-${instance}`;\n    const svg = `<svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 448 512\" style=\"width: 2rem; height: 2rem; vertical-align: top;\">\n        <path d=\"M400 32H48A48 48 0 0 0 0 80v352a48 48 0 0 0 48 48h352a48 48 0 0 0 48-48V80a48 48 0 0 0-48-48zm-51.37 182.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z\" class=\"svg-background\"/>\n        <path d=\"M348.63 214.31L232.06 348.16a10.38 10.38 0 0 1-16.12 0L99.37 214.31C92.17 206 97.28 192 107.43 192h233.14c10.15 0 15.26 14 8.06 22.31z\" class=\"svg-foreground\"/>\n      </svg>`;\n    if (title) elTitle.innerHTML = `${title}${svg}`;\n    this.menu.appendChild(elTitle);\n    elTitle.addEventListener('click', () => {\n      this.container.classList.toggle('menu-container-fadeout');\n      this.container.classList.toggle('menu-container-fadein');\n      this.menu.style.borderStyle = this.container.classList.contains('menu-container-fadeout') ? 'none' : 'solid';\n    });\n\n    this.menu.appendChild(this.container);\n    if (typeof parent === 'object') parent.appendChild(this.menu);\n    else document.getElementById(parent).appendChild(this.menu);\n  }\n\n  get newID() {\n    this.id++;\n    return `menu-${this.instance}-${this.id}`;\n  }\n\n  get ID() {\n    return `menu-${this.instance}-${this.id}`;\n  }\n\n  get width() {\n    return this.menu.offsetWidth;\n  }\n\n  get height() {\n    return this.menu.offsetHeight;\n  }\n\n  hide() {\n    if (this.container.classList.contains('menu-container-fadein')) {\n      this.container.classList.toggle('menu-container-fadeout');\n      this.container.classList.toggle('menu-container-fadein');\n    }\n  }\n\n  visible() {\n    return (this.container.classList.contains('menu-container-fadein'));\n  }\n\n  toggle(evt) {\n    this.container.classList.toggle('menu-container-fadeout');\n    this.container.classList.toggle('menu-container-fadein');\n    if (this.container.classList.contains('menu-container-fadein') && evt) {\n      const x = evt.x || (evt.touches && evt.touches[0] ? evt.touches[0].pageX : null);\n      // const y = evt.y || (evt.touches && evt.touches[0] ? evt.touches[0].pageY : null);\n      if (x) this.menu.style.left = `${x - (this.menu.offsetWidth / 2)}px`;\n      // if (y) this.menu.style.top = '5.5rem'; // `${evt.y + 55}px`;\n      if (this.menu.offsetLeft < 0) this.menu.style.left = 0;\n      if ((this.menu.offsetLeft + this.menu.offsetWidth) > window.innerWidth) {\n        this.menu.style.left = null;\n        this.menu.style.right = 0;\n      }\n      this.menu.style.borderStyle = 'solid';\n    } else {\n      this.menu.style.borderStyle = 'none';\n    }\n  }\n\n  addTitle(title) {\n    const el = document.createElement('div');\n    el.className = 'menu-title';\n    el.id = this.newID;\n    el.innerHTML = title;\n    this.menu.appendChild(el);\n    el.addEventListener('click', () => {\n      this.hidden = !this.hidden;\n      const all = document.getElementsByClassName('menu');\n      for (const item of all) {\n        item.style.display = this.hidden ? 'none' : 'block';\n      }\n    });\n    return el;\n  }\n\n  addLabel(title) {\n    const el = document.createElement('div');\n    el.className = 'menu-item menu-label';\n    el.id = this.newID;\n    el.innerHTML = title;\n    this.container.appendChild(el);\n    return el;\n  }\n\n  addBool(title, object, variable, callback) {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    el.innerHTML = `<div class=\"menu-checkbox\"><input class=\"menu-checkbox\" type=\"checkbox\" id=\"${this.newID}\" ${object[variable] ? 'checked' : ''}/><label class=\"menu-checkbox-label\" for=\"${this.ID}\"></label></div>${title}`;\n    this.container.appendChild(el);\n    el.addEventListener('change', (evt) => {\n      object[variable] = evt.target.checked;\n      if (callback) callback(evt.target.checked);\n    });\n    return el;\n  }\n\n  async addList(title, items, selected, callback) {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    let options = '';\n    for (const item of items) {\n      const def = item === selected ? 'selected' : '';\n      options += `<option value=\"${item}\" ${def}>${item}</option>`;\n    }\n    el.innerHTML = `<div class=\"menu-list\"><select name=\"${this.ID}\" class=\"menu-list-item\">${options}</select><label for=\"${this.ID}\"></label></div>${title}`;\n    el.style.fontFamily = document.body.style.fontFamily;\n    el.style.fontSize = document.body.style.fontSize;\n    el.style.fontVariant = document.body.style.fontVariant;\n    this.container.appendChild(el);\n    el.addEventListener('change', (evt) => {\n      if (callback) callback(items[evt.target.selectedIndex]);\n    });\n    return el;\n  }\n\n  addRange(title, object, variable, min, max, step, callback) {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    el.innerHTML = `<input class=\"menu-range\" type=\"range\" id=\"${this.newID}\" min=\"${min}\" max=\"${max}\" step=\"${step}\" value=\"${object[variable]}\">${title}`;\n    this.container.appendChild(el);\n    el.addEventListener('change', (evt) => {\n      object[variable] = parseInt(evt.target.value) === parseFloat(evt.target.value) ? parseInt(evt.target.value) : parseFloat(evt.target.value);\n      evt.target.setAttribute('value', evt.target.value);\n      if (callback) callback(evt.target.value);\n    });\n    el.input = el.children[0];\n    return el;\n  }\n\n  addHTML(html) {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    el.id = this.newID;\n    if (html) el.innerHTML = html;\n    this.container.appendChild(el);\n    return el;\n  }\n\n  addButton(titleOn, titleOff, callback) {\n    const el = document.createElement('button');\n    el.className = 'menu-item menu-button';\n    el.style.fontFamily = document.body.style.fontFamily;\n    el.style.fontSize = document.body.style.fontSize;\n    el.style.fontVariant = document.body.style.fontVariant;\n    el.type = 'button';\n    el.id = this.newID;\n    el.innerText = titleOn;\n    this.container.appendChild(el);\n    el.addEventListener('click', () => {\n      if (el.innerText === titleOn) el.innerText = titleOff;\n      else el.innerText = titleOn;\n      if (callback) callback(el.innerText !== titleOn);\n    });\n    return el;\n  }\n\n  addValue(title, val, suffix = '') {\n    const el = document.createElement('div');\n    el.className = 'menu-item';\n    el.id = `menu-val-${title}`;\n    el.innerText = `${title}: ${val}${suffix}`;\n    this.container.appendChild(el);\n    return el;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  updateValue(title, val, suffix = '') {\n    const el = document.getElementById(`menu-val-${title}`);\n    if (el) el.innerText = `${title}: ${val}${suffix}`;\n    else this.addValue(title, val);\n  }\n\n  addChart(title, id, width = 150, height = 40, color) {\n    if (color) theme.chartColor = color;\n    const el = document.createElement('div');\n    el.className = 'menu-item menu-chart-title';\n    el.id = this.newID;\n    el.innerHTML = `<font color=${theme.chartColor}>${title}</font><canvas id=\"menu-canvas-${id}\" class=\"menu-chart-canvas\" width=\"${width}px\" height=\"${height}px\"></canvas>`;\n    this.container.appendChild(el);\n    return el;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  async updateChart(id, values) {\n    if (!values || (values.length === 0)) return;\n    const canvas = document.getElementById(`menu-canvas-${id}`);\n    if (!canvas) return;\n    const ctx = canvas.getContext('2d');\n    ctx.fillStyle = theme.background;\n    ctx.fillRect(0, 0, canvas.width, canvas.height);\n    const width = canvas.width / values.length;\n    const max = 1 + Math.max(...values);\n    const height = canvas.height / max;\n    for (let i = 0; i < values.length; i++) {\n      const gradient = ctx.createLinearGradient(0, (max - values[i]) * height, 0, 0);\n      gradient.addColorStop(0.1, theme.chartColor);\n      gradient.addColorStop(0.4, theme.background);\n      ctx.fillStyle = gradient;\n      ctx.fillRect(i * width, 0, width - 4, canvas.height);\n      ctx.fillStyle = theme.background;\n      ctx.font = `${width / 1.5}px \"Segoe UI\"`;\n      ctx.fillText(Math.round(values[i]), i * width + 1, canvas.height - 1, width - 1);\n    }\n  }\n}\n\nexport default Menu;\n", "/* eslint-disable max-len */\n\n// based on: https://github.com/munrocket/gl-bench\n\nconst UICSS = `\n  #gl-bench { position: absolute; right: 1rem; bottom: 1rem; z-index:1000; -webkit-user-select: none; -moz-user-select: none; user-select: none; }\n  #gl-bench div { position: relative; display: block; margin: 4px; padding: 0 2px 0 2px; background: darkslategray; border-radius: 0.1rem; cursor: pointer; opacity: 0.9; }\n  #gl-bench svg { height: 60px; margin: 0 0px 0px 4px; }\n  #gl-bench text { font-size: 16px; font-family: 'Lato', 'Segoe UI'; dominant-baseline: middle; text-anchor: middle; }\n  #gl-bench .gl-mem { font-size: 12px; fill: white; }\n  #gl-bench .gl-fps { font-size: 13px; fill: white; }\n  #gl-bench line { stroke-width: 5; stroke: white; stroke-linecap: round; }\n  #gl-bench polyline { fill: none; stroke: white; stroke-linecap: round; stroke-linejoin: round; stroke-width: 3.5; }\n  #gl-bench rect { fill: black; }\n  #gl-bench .opacity { stroke: black; }\n  `;\n\nconst UISVG = `\n  <div class=\"gl-box\">\n    <svg viewBox=\"0 0 60 60\">\n      <text x=\"27\" y=\"56\" class=\"gl-fps\">00 FPS</text>\n      <text x=\"30\" y=\"8\" class=\"gl-mem\"></text>\n      <rect x=\"0\" y=\"14\" rx=\"4\" ry=\"4\" width=\"60\" height=\"32\"></rect>\n      <polyline class=\"gl-chart\"></polyline>\n    </svg>\n    <svg viewBox=\"0 0 14 60\" class=\"gl-cpu-svg\">\n      <line x1=\"7\" y1=\"38\" x2=\"7\" y2=\"11\" class=\"opacity\"/>\n      <line x1=\"7\" y1=\"38\" x2=\"7\" y2=\"11\" class=\"gl-cpu\" stroke-dasharray=\"0 27\"/>\n      <path d=\"M5.35 43c-.464 0-.812.377-.812.812v1.16c-.783.1972-1.421.812-1.595 1.624h-1.16c-.435 0-.812.348-.812.812s.348.812.812.812h1.102v1.653H1.812c-.464 0-.812.377-.812.812 0 .464.377.812.812.812h1.131c.1943.783.812 1.392 1.595 1.595v1.131c0 .464.377.812.812.812.464 0 .812-.377.812-.812V53.15h1.653v1.073c0 .464.377.812.812.812.464 0 .812-.377.812-.812v-1.131c.783-.1943 1.392-.812 1.595-1.595h1.131c.464 0 .812-.377.812-.812 0-.464-.377-.812-.812-.812h-1.073V48.22h1.102c.435 0 .812-.348.812-.812s-.348-.812-.812-.812h-1.16c-.1885-.783-.812-1.421-1.595-1.624v-1.131c0-.464-.377-.812-.812-.812-.464 0-.812.377-.812.812v1.073H6.162v-1.073c0-.464-.377-.812-.812-.812zm.58 3.48h2.088c.754 0 1.363.609 1.363 1.363v2.088c0 .754-.609 1.363-1.363 1.363H5.93c-.754 0-1.363-.609-1.363-1.363v-2.088c0-.754.609-1.363 1.363-1.363z\" style=\"fill: grey\"></path>\n    </svg>\n    <svg viewBox=\"0 0 14 60\" class=\"gl-gpu-svg\">\n      <line x1=\"7\" y1=\"38\" x2=\"7\" y2=\"11\" class=\"opacity\"/>\n      <line x1=\"7\" y1=\"38\" x2=\"7\" y2=\"11\" class=\"gl-gpu\" stroke-dasharray=\"0 27\"/>\n      <path d=\"M1.94775 43.3772a.736.736 0 10-.00416 1.472c.58535.00231.56465.1288.6348.3197.07015.18975.04933.43585.04933.43585l-.00653.05405v8.671a.736.736 0 101.472 0v-1.4145c.253.09522.52785.1495.81765.1495h5.267c1.2535 0 2.254-.9752 2.254-2.185v-3.105c0-1.2075-1.00625-2.185-2.254-2.185h-5.267c-.28865 0-.5635.05405-.8165.1495.01806-.16445.04209-.598-.1357-1.0787-.22425-.6072-.9499-1.2765-2.0125-1.2765zm2.9095 3.6455c.42435 0 .7659.36225.7659.8119v2.9785c0 .44965-.34155.8119-.7659.8119s-.7659-.36225-.7659-.8119v-2.9785c0-.44965.34155-.8119.7659-.8119zm4.117 0a2.3 2.3 0 012.3 2.3 2.3 2.3 0 01-2.3 2.3 2.3 2.3 0 01-2.3-2.3 2.3 2.3 0 012.3-2.3z\" style=\"fill: grey\"></path>\n    </svg>\n  </div>\n  `;\n\nclass GLBench {\n  /** GLBench constructor\n   * @param { WebGLRenderingContext | WebGL2RenderingContext } gl context\n   * @param { Object | undefined } settings additional settings\n   */\n  constructor(gl, settings = {}) {\n    this.css = UICSS;\n    this.svg = UISVG;\n    // eslint-disable-next-line @typescript-eslint/no-empty-function\n    this.paramLogger = () => {};\n    // eslint-disable-next-line @typescript-eslint/no-empty-function\n    this.chartLogger = () => {};\n    this.chartLen = 20;\n    this.chartHz = 20;\n\n    this.names = [];\n    this.cpuAccums = [];\n    this.gpuAccums = [];\n    this.activeAccums = [];\n    this.chart = new Array(this.chartLen);\n    this.now = () => ((performance && performance.now) ? performance.now() : Date.now());\n    this.updateUI = () => {\n      [].forEach.call(this.nodes['gl-gpu-svg'], (node) => node.style.display = this.trackGPU ? 'inline' : 'none');\n    };\n\n    Object.assign(this, settings);\n    this.detected = 0;\n    this.finished = [];\n    this.isFramebuffer = 0;\n    this.frameId = 0;\n\n    // 120hz device detection\n    let rafId; let n = 0; let\n      t0;\n    const loop = (t) => {\n      if (++n < 20) {\n        rafId = requestAnimationFrame(loop);\n      } else {\n        this.detected = Math.ceil(1e3 * n / (t - t0) / 70);\n        cancelAnimationFrame(rafId);\n      }\n      if (!t0) t0 = t;\n    };\n    requestAnimationFrame(loop);\n\n    // attach gpu profilers\n    if (gl) {\n      const glFinish = async (t, activeAccums) => Promise.resolve(setTimeout(() => {\n        gl.getError();\n        const dt = this.now() - t;\n        activeAccums.forEach((active, i) => {\n          if (active) this.gpuAccums[i] += dt;\n        });\n      }, 0));\n\n      const addProfiler = (fn, self, target) => {\n        const t = self.now();\n        // eslint-disable-next-line prefer-rest-params\n        fn.apply(target, arguments);\n        if (self.trackGPU) self.finished.push(glFinish(t, self.activeAccums.slice(0)));\n      };\n\n      /* ['drawArrays', 'drawElements', 'drawArraysInstanced', 'drawBuffers', 'drawElementsInstanced', 'drawRangeElements'].forEach((fn) => {\n        if (gl[fn]) {\n          gl[fn] = addProfiler(gl[fn], this, gl);\n        }\n      });\n      */\n      const fn = 'drawElements';\n      if (gl[fn]) {\n        gl[fn] = addProfiler(gl[fn], this, gl);\n      } else {\n        // eslint-disable-next-line no-console\n        console.log('bench: cannot attach to webgl function');\n      }\n\n      /*\n      gl.getExtension = ((fn, self) => {\n        // eslint-disable-next-line prefer-rest-params\n        const ext = fn.apply(gl, arguments);\n        if (ext) {\n          ['drawElementsInstancedANGLE', 'drawBuffersWEBGL'].forEach((fn2) => {\n            if (ext[fn2]) {\n              ext[fn2] = addProfiler(ext[fn2], self, ext);\n            }\n          });\n        }\n        return ext;\n      })(gl.getExtension, this);\n      */\n    }\n\n    // init ui and ui loggers\n    if (!this.withoutUI) {\n      if (!this.dom) this.dom = document.body;\n      const elm = document.createElement('div');\n      elm.id = 'gl-bench';\n      this.dom.appendChild(elm);\n      this.dom.insertAdjacentHTML('afterbegin', '<style id=\"gl-bench-style\">' + this.css + '</style>');\n      this.dom = elm;\n      this.dom.addEventListener('click', () => {\n        this.trackGPU = !this.trackGPU;\n        this.updateUI();\n      });\n\n      this.paramLogger = ((logger, dom, names) => {\n        const classes = ['gl-cpu', 'gl-gpu', 'gl-mem', 'gl-fps', 'gl-gpu-svg', 'gl-chart'];\n        const nodes = { ...classes };\n        classes.forEach((c) => nodes[c] = dom.getElementsByClassName(c));\n        this.nodes = nodes;\n        return (i, cpu, gpu, mem, fps, totalTime, frameId) => {\n          nodes['gl-cpu'][i].style.strokeDasharray = (cpu * 0.27).toFixed(0) + ' 100';\n          nodes['gl-gpu'][i].style.strokeDasharray = (gpu * 0.27).toFixed(0) + ' 100';\n          // eslint-disable-next-line no-nested-ternary\n          nodes['gl-mem'][i].innerHTML = names[i] ? names[i] : (mem ? 'mem: ' + mem.toFixed(0) + 'mb' : '');\n          nodes['gl-fps'][i].innerHTML = 'FPS: ' + fps.toFixed(1);\n          logger(names[i], cpu, gpu, mem, fps, totalTime, frameId);\n        };\n      })(this.paramLogger, this.dom, this.names);\n\n      this.chartLogger = ((logger, dom) => {\n        const nodes = { 'gl-chart': dom.getElementsByClassName('gl-chart') };\n        return (i, chart, circularId) => {\n          let points = '';\n          const len = chart.length;\n          for (let j = 0; j < len; j++) {\n            const id = (circularId + j + 1) % len;\n            if (chart[id] !== undefined) points = points + ' ' + (60 * j / (len - 1)).toFixed(1) + ',' + (45 - chart[id] * 0.5 / this.detected).toFixed(1);\n          }\n          nodes['gl-chart'][i].setAttribute('points', points);\n          logger(this.names[i], chart, circularId);\n        };\n      })(this.chartLogger, this.dom);\n    }\n  }\n\n  /**\n   * Explicit UI add\n   * @param { string | undefined } name\n   */\n  addUI(name) {\n    if (this.names.indexOf(name) === -1) {\n      this.names.push(name);\n      if (this.dom) {\n        this.dom.insertAdjacentHTML('beforeend', this.svg);\n        this.updateUI();\n      }\n      this.cpuAccums.push(0);\n      this.gpuAccums.push(0);\n      this.activeAccums.push(false);\n    }\n  }\n\n  /**\n   * Increase frameID\n   * @param { number | undefined } now\n   */\n  nextFrame(now) {\n    this.frameId++;\n    const t = now || this.now();\n\n    // params\n    if (this.frameId <= 1) {\n      this.paramFrame = this.frameId;\n      this.paramTime = t;\n    } else {\n      const duration = t - this.paramTime;\n      if (duration >= 1e3) {\n        const frameCount = this.frameId - this.paramFrame;\n        const fps = frameCount / duration * 1e3;\n        for (let i = 0; i < this.names.length; i++) {\n          const cpu = this.cpuAccums[i] / duration * 100;\n          const gpu = this.gpuAccums[i] / duration * 100;\n          const mem = (performance && performance.memory) ? performance.memory.usedJSHeapSize / (1 << 20) : 0;\n          this.paramLogger(i, cpu, gpu, mem, fps, duration, frameCount);\n          this.cpuAccums[i] = 0;\n          Promise.all(this.finished).then(() => {\n            this.gpuAccums[i] = 0;\n            this.finished = [];\n          });\n        }\n        this.paramFrame = this.frameId;\n        this.paramTime = t;\n      }\n    }\n\n    // chart\n    if (!this.detected || !this.chartFrame) {\n      this.chartFrame = this.frameId;\n      this.chartTime = t;\n      this.circularId = 0;\n    } else {\n      const timespan = t - this.chartTime;\n      let hz = this.chartHz * timespan / 1e3;\n      while (--hz > 0 && this.detected) {\n        const frameCount = this.frameId - this.chartFrame;\n        const fps = frameCount / timespan * 1e3;\n        this.chart[this.circularId % this.chartLen] = fps;\n        for (let i = 0; i < this.names.length; i++) this.chartLogger(i, this.chart, this.circularId);\n        this.circularId++;\n        this.chartFrame = this.frameId;\n        this.chartTime = t;\n      }\n    }\n  }\n\n  /**\n   * Begin named measurement\n   * @param { string | undefined } name\n   */\n  begin(name) {\n    this.updateAccums(name);\n  }\n\n  /**\n   * End named measure\n   * @param { string | undefined } name\n   */\n  end(name) {\n    this.updateAccums(name);\n  }\n\n  updateAccums(name) {\n    let nameId = this.names.indexOf(name);\n    if (nameId === -1) {\n      nameId = this.names.length;\n      this.addUI(name);\n    }\n\n    const t = this.now();\n    const dt = t - this.t0;\n    for (let i = 0; i < nameId + 1; i++) {\n      if (this.activeAccums[i]) this.cpuAccums[i] += dt;\n    }\n    this.activeAccums[nameId] = !this.activeAccums[nameId];\n    this.t0 = t;\n  }\n}\n\nexport default GLBench;\n", "// import Human from '../dist/human.esm.js'; // equivalent of @vladmandic/human\nimport Human from '../src/human';\nimport Menu from './menu.js';\nimport GLBench from './gl-bench.js';\n\nconst userConfig = { backend: 'webgl' }; // add any user configuration overrides\n\n/*\nconst userConfig = {\n  backend: 'wasm',\n  async: false,\n  warmup: 'full',\n  videoOptimized: true,\n  filter: { enabled: true },\n  face: { enabled: true, mesh: { enabled: true }, iris: { enabled: false }, age: { enabled: false }, gender: { enabled: false }, emotion: { enabled: false }, embedding: { enabled: false } },\n  hand: { enabled: false },\n  gesture: { enabled: false },\n  body: { enabled: false, modelPath: '../models/blazepose.json' },\n  object: { enabled: false },\n};\n*/\n\nconst human = new Human(userConfig);\n\n// ui options\nconst ui = {\n  baseBackground: 'rgba(50, 50, 50, 1)', // 'grey'\n  crop: true, // video mode crop to size or leave full frame\n  columns: 2, // when processing sample images create this many columns\n  facing: true, // camera facing front or back\n  useWorker: false, // use web workers for processing\n  worker: 'worker.js',\n  samples: ['../assets/sample6.jpg', '../assets/sample1.jpg', '../assets/sample4.jpg', '../assets/sample5.jpg', '../assets/sample3.jpg', '../assets/sample2.jpg'],\n  compare: '../assets/sample-me.jpg',\n  console: true, // log messages to browser console\n  maxFPSframes: 10, // keep fps history for how many frames\n  modelsPreload: true, // preload human models on startup\n  busy: false, // internal camera busy flag\n  menuWidth: 0, // internal\n  menuHeight: 0, // internal\n  camera: {}, // internal, holds details of webcam details\n  detectFPS: [], // internal, holds fps values for detection performance\n  drawFPS: [], // internal, holds fps values for draw performance\n  buffered: false, // experimental, should output be buffered between frames\n  drawWarmup: false, // debug only, should warmup image processing be displayed on startup\n  drawThread: null, // internl, perform draw operations in a separate thread\n  detectThread: null, // internl, perform detect operations in a separate thread\n  framesDraw: 0, // internal, statistics on frames drawn\n  framesDetect: 0, // internal, statistics on frames detected\n  bench: true, // show gl fps benchmark window\n  lastFrame: 0, // time of last frame processing\n};\n\n// global variables\nconst menu = {};\nlet worker;\nlet bench;\nlet lastDetectedResult = {};\n\n// helper function: translates json to human readable string\nfunction str(...msg) {\n  if (!Array.isArray(msg)) return msg;\n  let line = '';\n  for (const entry of msg) {\n    if (typeof entry === 'object') line += JSON.stringify(entry).replace(/{|}|\"|\\[|\\]/g, '').replace(/,/g, ', ');\n    else line += entry;\n  }\n  return line;\n}\n\n// helper function: wrapper around console output\nfunction log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (ui.console) console.log(ts, ...msg);\n}\n\nfunction status(msg) {\n  // eslint-disable-next-line no-console\n  const div = document.getElementById('status');\n  if (div) div.innerText = msg;\n}\n\nlet original;\nasync function calcSimmilariry(result) {\n  document.getElementById('compare-container').style.display = human.config.face.embedding.enabled ? 'block' : 'none';\n  if (!human.config.face.embedding.enabled) return;\n  if (!(result?.face?.length > 0) || (result?.face[0]?.embedding?.length >= 64)) return;\n  if (!original) {\n    original = result;\n    if (result.face[0].tensor) {\n      const enhanced = human.enhance(result.face[0]);\n      if (enhanced) {\n        const c = document.getElementById('orig');\n        const squeeze = enhanced.squeeze();\n        human.tf.browser.toPixels(squeeze, c);\n        enhanced.dispose();\n        squeeze.dispose();\n      }\n    } else {\n      document.getElementById('compare-canvas').getContext('2d').drawImage(original.canvas, 0, 0, 200, 200);\n    }\n  }\n  const simmilarity = human.simmilarity(original?.face[0]?.embedding, result?.face[0]?.embedding);\n  document.getElementById('simmilarity').innerText = `simmilarity: ${Math.trunc(1000 * simmilarity) / 10}%`;\n}\n\n// draws processed results and starts processing of a next frame\nlet lastDraw = performance.now();\nasync function drawResults(input) {\n  const result = lastDetectedResult;\n  const canvas = document.getElementById('canvas');\n\n  // update draw fps data\n  ui.drawFPS.push(1000 / (performance.now() - lastDraw));\n  if (ui.drawFPS.length > ui.maxFPSframes) ui.drawFPS.shift();\n  lastDraw = performance.now();\n\n  // draw fps chart\n  await menu.process.updateChart('FPS', ui.detectFPS);\n\n  // get updated canvas\n  if (ui.buffered || !result.canvas) {\n    const image = await human.image(input);\n    result.canvas = image.canvas;\n    human.tf.dispose(image.tensor);\n  }\n\n  // draw image from video\n  const ctx = canvas.getContext('2d');\n  ctx.fillStyle = ui.baseBackground;\n  ctx.fillRect(0, 0, canvas.width, canvas.height);\n  if (result.canvas) {\n    if (result.canvas.width !== canvas.width) canvas.width = result.canvas.width;\n    if (result.canvas.height !== canvas.height) canvas.height = result.canvas.height;\n    ctx.drawImage(result.canvas, 0, 0, result.canvas.width, result.canvas.height, 0, 0, result.canvas.width, result.canvas.height);\n  } else {\n    ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);\n  }\n\n  // draw all results\n  human.draw.face(canvas, result.face);\n  human.draw.body(canvas, result.body);\n  human.draw.hand(canvas, result.hand);\n  human.draw.object(canvas, result.object);\n  human.draw.gesture(canvas, result.gesture);\n  await calcSimmilariry(result);\n\n  // update log\n  const engine = human.tf.engine();\n  const gpu = engine.backendInstance ? `gpu: ${(engine.backendInstance.numBytesInGPU ? engine.backendInstance.numBytesInGPU : 0).toLocaleString()} bytes` : '';\n  const memory = `system: ${engine.state.numBytes.toLocaleString()} bytes ${gpu} | tensors: ${engine.state.numTensors.toLocaleString()}`;\n  const processing = result.canvas ? `processing: ${result.canvas.width} x ${result.canvas.height}` : '';\n  const avgDetect = Math.trunc(10 * ui.detectFPS.reduce((a, b) => a + b, 0) / ui.detectFPS.length) / 10;\n  const avgDraw = Math.trunc(10 * ui.drawFPS.reduce((a, b) => a + b, 0) / ui.drawFPS.length) / 10;\n  const warning = (ui.detectFPS.length > 5) && (avgDetect < 5) ? '<font color=\"lightcoral\">warning: your performance is low: try switching to higher performance backend, lowering resolution or disabling some models</font>' : '';\n  document.getElementById('log').innerHTML = `\n    video: ${ui.camera.name} | facing: ${ui.camera.facing} | screen: ${window.innerWidth} x ${window.innerHeight} camera: ${ui.camera.width} x ${ui.camera.height} ${processing}<br>\n    backend: ${human.tf.getBackend()} | ${memory}<br>\n    performance: ${str(result.performance)}ms FPS process:${avgDetect} refresh:${avgDraw}<br>\n    ${warning}<br>\n  `;\n\n  ui.framesDraw++;\n  ui.lastFrame = performance.now();\n  // if buffered, immediate loop but limit frame rate although it's going to run slower as JS is singlethreaded\n  if (ui.buffered) {\n    ui.drawThread = requestAnimationFrame(() => drawResults(input, canvas));\n  } else if (!ui.buffered && ui.drawThread) {\n    log('stopping buffered refresh');\n    cancelAnimationFrame(ui.drawThread);\n    ui.drawThread = null;\n  }\n}\n\n// setup webcam\nasync function setupCamera() {\n  if (ui.busy) return null;\n  ui.busy = true;\n  const video = document.getElementById('video');\n  const canvas = document.getElementById('canvas');\n  const output = document.getElementById('log');\n  const live = video.srcObject ? ((video.srcObject.getVideoTracks()[0].readyState === 'live') && (video.readyState > 2) && (!video.paused)) : false;\n  let msg = '';\n  status('setting up camera');\n  // setup webcam. note that navigator.mediaDevices requires that page is accessed via https\n  if (!navigator.mediaDevices) {\n    msg = 'camera access not supported';\n    output.innerText += `\\n${msg}`;\n    log(msg);\n    status(msg);\n    ui.busy = false;\n    return msg;\n  }\n  let stream;\n  const constraints = {\n    audio: false,\n    video: { facingMode: ui.facing ? 'user' : 'environment', resizeMode: ui.crop ? 'crop-and-scale' : 'none' },\n  };\n  if (window.innerWidth > window.innerHeight) constraints.video.width = { ideal: window.innerWidth };\n  else constraints.video.height = { ideal: (window.innerHeight - document.getElementById('menubar').offsetHeight) };\n  try {\n    stream = await navigator.mediaDevices.getUserMedia(constraints);\n  } catch (err) {\n    if (err.name === 'PermissionDeniedError' || err.name === 'NotAllowedError') msg = 'camera permission denied';\n    else if (err.name === 'SourceUnavailableError') msg = 'camera not available';\n    else msg = `camera error: ${err.message || err}`;\n    output.innerText += `\\n${msg}`;\n    status(msg);\n    log('camera error:', err);\n    ui.busy = false;\n    return msg;\n  }\n  if (stream) video.srcObject = stream;\n  else {\n    ui.busy = false;\n    return 'camera stream empty';\n  }\n  const track = stream.getVideoTracks()[0];\n  const settings = track.getSettings();\n  // log('camera constraints:', constraints, 'window:', { width: window.innerWidth, height: window.innerHeight }, 'settings:', settings, 'track:', track);\n  ui.camera = { name: track.label?.toLowerCase(), width: settings.width, height: settings.height, facing: settings.facingMode === 'user' ? 'front' : 'back' };\n  return new Promise((resolve) => {\n    video.onloadeddata = async () => {\n      video.width = video.videoWidth;\n      video.height = video.videoHeight;\n      canvas.width = video.width;\n      canvas.height = video.height;\n      canvas.style.width = canvas.width > canvas.height ? '100vw' : '';\n      canvas.style.height = canvas.width > canvas.height ? '' : '100vh';\n      ui.menuWidth.input.setAttribute('value', video.width);\n      ui.menuHeight.input.setAttribute('value', video.height);\n      // silly font resizing for paint-on-canvas since viewport can be zoomed\n      if (live) video.play();\n      // eslint-disable-next-line no-use-before-define\n      if (live && !ui.detectThread) runHumanDetect(video, canvas);\n      ui.busy = false;\n      // do once more because onresize events can be delayed or skipped\n      // if (video.width > window.innerWidth) await setupCamera();\n      status('');\n      resolve();\n    };\n  });\n}\n\nfunction initPerfMonitor() {\n  if (!bench) {\n    const gl = null;\n    // cosnt gl = human.tf.engine().backend.gpgpu.gl;\n    // if (!gl) log('bench cannot get tensorflow webgl context');\n    bench = new GLBench(gl, {\n      trackGPU: false, // this is really slow\n      chartHz: 20,\n      chartLen: 20,\n    });\n    bench.begin();\n  }\n}\n\n// wrapper for worker.postmessage that creates worker if one does not exist\nfunction webWorker(input, image, canvas, timestamp) {\n  if (!worker) {\n    // create new webworker and add event handler only once\n    log('creating worker thread');\n    worker = new Worker(ui.worker, { type: 'module' });\n    // after receiving message from webworker, parse&draw results and send new frame for processing\n    worker.addEventListener('message', (msg) => {\n      if (msg.data.result.performance && msg.data.result.performance.total) ui.detectFPS.push(1000 / msg.data.result.performance.total);\n      if (ui.detectFPS.length > ui.maxFPSframes) ui.detectFPS.shift();\n      if (ui.bench) {\n        if (!bench) initPerfMonitor();\n        bench.nextFrame(timestamp);\n      }\n      if (document.getElementById('gl-bench')) document.getElementById('gl-bench').style.display = ui.bench ? 'block' : 'none';\n      lastDetectedResult = msg.data.result;\n      ui.framesDetect++;\n      if (!ui.drawThread) drawResults(input);\n      // eslint-disable-next-line no-use-before-define\n      ui.detectThread = requestAnimationFrame((now) => runHumanDetect(input, canvas, now));\n    });\n  }\n  // pass image data as arraybuffer to worker by reference to avoid copy\n  worker.postMessage({ image: image.data.buffer, width: canvas.width, height: canvas.height, userConfig }, [image.data.buffer]);\n}\n\n// main processing function when input is webcam, can use direct invocation or web worker\nfunction runHumanDetect(input, canvas, timestamp) {\n  // if live video\n  const live = input.srcObject && (input.srcObject.getVideoTracks()[0].readyState === 'live') && (input.readyState > 2) && (!input.paused);\n  if (!live && input.srcObject) {\n    // stop ui refresh\n    if (ui.drawThread) cancelAnimationFrame(ui.drawThread);\n    if (ui.detectThread) cancelAnimationFrame(ui.detectThread);\n    ui.drawThread = null;\n    ui.detectThread = null;\n    // if we want to continue and camera not ready, retry in 0.5sec, else just give up\n    if (input.paused) log('camera paused');\n    else if ((input.srcObject.getVideoTracks()[0].readyState === 'live') && (input.readyState <= 2)) setTimeout(() => runHumanDetect(input, canvas), 500);\n    else log(`camera not ready: track state: ${input.srcObject?.getVideoTracks()[0].readyState} stream state: ${input.readyState}`);\n    clearTimeout(ui.drawThread);\n    ui.drawThread = null;\n    log('frame statistics: process:', ui.framesDetect, 'refresh:', ui.framesDraw);\n    log('memory', human.tf.engine().memory());\n    return;\n  }\n  status('');\n  if (ui.useWorker) {\n    // get image data from video as we cannot send html objects to webworker\n    const offscreen = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(canvas.width, canvas.height) : document.createElement('canvas');\n    offscreen.width = canvas.width;\n    offscreen.height = canvas.height;\n    const ctx = offscreen.getContext('2d');\n    ctx.drawImage(input, 0, 0, input.width, input.height, 0, 0, canvas.width, canvas.height);\n    const data = ctx.getImageData(0, 0, canvas.width, canvas.height);\n    // perform detection in worker\n    webWorker(input, data, canvas, userConfig, timestamp);\n  } else {\n    human.detect(input, userConfig).then((result) => {\n      if (result.performance && result.performance.total) ui.detectFPS.push(1000 / result.performance.total);\n      if (ui.detectFPS.length > ui.maxFPSframes) ui.detectFPS.shift();\n      if (ui.bench) {\n        if (!bench) initPerfMonitor();\n        bench.nextFrame(timestamp);\n      }\n      if (document.getElementById('gl-bench')) document.getElementById('gl-bench').style.display = ui.bench ? 'block' : 'none';\n      if (result.error) {\n        log(result.error);\n        document.getElementById('log').innerText += `\\nHuman error: ${result.error}`;\n      } else {\n        lastDetectedResult = result;\n        if (!ui.drawThread) drawResults(input);\n        ui.framesDetect++;\n        ui.detectThread = requestAnimationFrame((now) => runHumanDetect(input, canvas, now));\n      }\n    });\n  }\n}\n\n// main processing function when input is image, can use direct invocation or web worker\nasync function processImage(input) {\n  return new Promise((resolve) => {\n    const image = new Image();\n    image.onload = async () => {\n      log('Processing image:', encodeURI(image.src));\n      const canvas = document.getElementById('canvas');\n      image.width = image.naturalWidth;\n      image.height = image.naturalHeight;\n      canvas.width = human.config.filter.width && human.config.filter.width > 0 ? human.config.filter.width : image.naturalWidth;\n      canvas.height = human.config.filter.height && human.config.filter.height > 0 ? human.config.filter.height : image.naturalHeight;\n      const result = await human.detect(image, userConfig);\n      lastDetectedResult = result;\n      await drawResults(image);\n      const thumb = document.createElement('canvas');\n      thumb.className = 'thumbnail';\n      thumb.width = window.innerWidth / (ui.columns + 0.1);\n      thumb.height = thumb.width * canvas.height / canvas.width;\n      if (result.face && result.face.length > 0) {\n        thumb.title = result.face.map((a, i) => `#${i} face: ${Math.trunc(100 * a.faceConfidence)}% box: ${Math.trunc(100 * a.boxConfidence)}% age: ${Math.trunc(a.age)} gender: ${Math.trunc(100 * a.genderConfidence)}% ${a.gender}`).join(' | ');\n      } else {\n        thumb.title = 'no face detected';\n      }\n      const ctx = thumb.getContext('2d');\n      ctx.drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, thumb.width, thumb.height);\n      document.getElementById('samples-container').appendChild(thumb);\n      image.src = '';\n      resolve(true);\n    };\n    image.src = input;\n  });\n}\n\n// just initialize everything and call main function\nasync function detectVideo() {\n  document.getElementById('samples-container').style.display = 'none';\n  document.getElementById('canvas').style.display = 'block';\n  const video = document.getElementById('video');\n  const canvas = document.getElementById('canvas');\n  if ((video.srcObject !== null) && !video.paused) {\n    document.getElementById('play').style.display = 'block';\n    document.getElementById('btnStart').className = 'button button-start';\n    document.getElementById('btnStart').innerHTML = 'start<br>video';\n    status('paused');\n    video.pause();\n  } else {\n    const cameraError = await setupCamera();\n    if (!cameraError) {\n      document.getElementById('play').style.display = 'none';\n      for (const m of Object.values(menu)) m.hide();\n      status('');\n      document.getElementById('btnStart').className = 'button button-stop';\n      document.getElementById('btnStart').innerHTML = 'pause<br>video';\n      await video.play();\n      if (!ui.detectThread) runHumanDetect(video, canvas);\n    } else {\n      status(cameraError);\n    }\n  }\n}\n\n// just initialize everything and call main function\nasync function detectSampleImages() {\n  userConfig.videoOptimized = false; // force disable video optimizations\n  document.getElementById('play').style.display = 'none';\n  document.getElementById('canvas').style.display = 'none';\n  document.getElementById('samples-container').style.display = 'block';\n  log('Running detection of sample images');\n  status('processing images');\n  document.getElementById('samples-container').innerHTML = '';\n  for (const m of Object.values(menu)) m.hide();\n  for (const image of ui.samples) await processImage(image);\n  status('');\n}\n\nfunction setupMenu() {\n  let x = [];\n  if (window.innerWidth > 800) {\n    // initial position of menu items, later it's calculated based on mouse coordinates\n    x = [`${document.getElementById('btnDisplay').offsetLeft - 50}px`, `${document.getElementById('btnImage').offsetLeft - 50}px`, `${document.getElementById('btnProcess').offsetLeft - 50}px`, `${document.getElementById('btnModel').offsetLeft - 50}px`];\n  } else {\n    // absolute minimum spacing for menus\n    x = ['0rem', '11rem', '21.1rem', '33rem'];\n  }\n\n  menu.display = new Menu(document.body, '', { top: `${document.getElementById('menubar').offsetHeight}px`, left: x[0] });\n  menu.display.addBool('perf monitor', ui, 'bench', (val) => ui.bench = val);\n  menu.display.addBool('buffered output', ui, 'buffered', (val) => ui.buffered = val);\n  menu.display.addBool('crop & scale', ui, 'crop', (val) => {\n    ui.crop = val;\n    setupCamera();\n  });\n  menu.display.addBool('camera facing', ui, 'facing', (val) => {\n    ui.facing = val;\n    setupCamera();\n  });\n  menu.display.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.display.addBool('use 3D depth', human.draw.drawOptions, 'useDepth');\n  menu.display.addBool('draw with curves', human.draw.drawOptions, 'useCurves');\n  menu.display.addBool('print labels', human.draw.drawOptions, 'drawLabels');\n  menu.display.addBool('draw points', human.draw.drawOptions, 'drawPoints');\n  menu.display.addBool('draw boxes', human.draw.drawOptions, 'drawBoxes');\n  menu.display.addBool('draw polygons', human.draw.drawOptions, 'drawPolygons');\n  menu.display.addBool('fill polygons', human.draw.drawOptions, 'fillPolygons');\n\n  menu.image = new Menu(document.body, '', { top: `${document.getElementById('menubar').offsetHeight}px`, left: x[1] });\n  menu.image.addBool('enabled', human.config.filter, 'enabled', (val) => human.config.filter.enabled = val);\n  ui.menuWidth = menu.image.addRange('image width', human.config.filter, 'width', 0, 3840, 10, (val) => human.config.filter.width = parseInt(val));\n  ui.menuHeight = menu.image.addRange('image height', human.config.filter, 'height', 0, 2160, 10, (val) => human.config.filter.height = parseInt(val));\n  menu.image.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.image.addRange('brightness', human.config.filter, 'brightness', -1.0, 1.0, 0.05, (val) => human.config.filter.brightness = parseFloat(val));\n  menu.image.addRange('contrast', human.config.filter, 'contrast', -1.0, 1.0, 0.05, (val) => human.config.filter.contrast = parseFloat(val));\n  menu.image.addRange('sharpness', human.config.filter, 'sharpness', 0, 1.0, 0.05, (val) => human.config.filter.sharpness = parseFloat(val));\n  menu.image.addRange('blur', human.config.filter, 'blur', 0, 20, 1, (val) => human.config.filter.blur = parseInt(val));\n  menu.image.addRange('saturation', human.config.filter, 'saturation', -1.0, 1.0, 0.05, (val) => human.config.filter.saturation = parseFloat(val));\n  menu.image.addRange('hue', human.config.filter, 'hue', 0, 360, 5, (val) => human.config.filter.hue = parseInt(val));\n  menu.image.addRange('pixelate', human.config.filter, 'pixelate', 0, 32, 1, (val) => human.config.filter.pixelate = parseInt(val));\n  menu.image.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.image.addBool('negative', human.config.filter, 'negative', (val) => human.config.filter.negative = val);\n  menu.image.addBool('sepia', human.config.filter, 'sepia', (val) => human.config.filter.sepia = val);\n  menu.image.addBool('vintage', human.config.filter, 'vintage', (val) => human.config.filter.vintage = val);\n  menu.image.addBool('kodachrome', human.config.filter, 'kodachrome', (val) => human.config.filter.kodachrome = val);\n  menu.image.addBool('technicolor', human.config.filter, 'technicolor', (val) => human.config.filter.technicolor = val);\n  menu.image.addBool('polaroid', human.config.filter, 'polaroid', (val) => human.config.filter.polaroid = val);\n\n  menu.process = new Menu(document.body, '', { top: `${document.getElementById('menubar').offsetHeight}px`, left: x[2] });\n  menu.process.addList('backend', ['cpu', 'webgl', 'wasm', 'humangl'], human.config.backend, (val) => human.config.backend = val);\n  menu.process.addBool('async operations', human.config, 'async', (val) => human.config.async = val);\n  // menu.process.addBool('enable profiler', human.config, 'profile', (val) => human.config.profile = val);\n  // menu.process.addBool('memory shield', human.config, 'deallocate', (val) => human.config.deallocate = val);\n  menu.process.addBool('use web worker', ui, 'useWorker');\n  menu.process.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.process.addLabel('model parameters');\n  menu.process.addRange('max objects', human.config.face.detector, 'maxFaces', 1, 50, 1, (val) => {\n    human.config.face.detector.maxFaces = parseInt(val);\n    human.config.body.maxDetections = parseInt(val);\n    human.config.hand.maxHands = parseInt(val);\n  });\n  menu.process.addRange('skip frames', human.config.face.detector, 'skipFrames', 0, 50, 1, (val) => {\n    human.config.face.detector.skipFrames = parseInt(val);\n    human.config.face.emotion.skipFrames = parseInt(val);\n    human.config.face.age.skipFrames = parseInt(val);\n    human.config.hand.skipFrames = parseInt(val);\n  });\n  menu.process.addRange('min confidence', human.config.face.detector, 'minConfidence', 0.0, 1.0, 0.05, (val) => {\n    human.config.face.detector.minConfidence = parseFloat(val);\n    human.config.face.gender.minConfidence = parseFloat(val);\n    human.config.face.emotion.minConfidence = parseFloat(val);\n    human.config.hand.minConfidence = parseFloat(val);\n  });\n  menu.process.addRange('score threshold', human.config.face.detector, 'scoreThreshold', 0.1, 1.0, 0.05, (val) => {\n    human.config.face.detector.scoreThreshold = parseFloat(val);\n    human.config.hand.scoreThreshold = parseFloat(val);\n    human.config.body.scoreThreshold = parseFloat(val);\n  });\n  menu.process.addRange('overlap', human.config.face.detector, 'iouThreshold', 0.1, 1.0, 0.05, (val) => {\n    human.config.face.detector.iouThreshold = parseFloat(val);\n    human.config.hand.iouThreshold = parseFloat(val);\n  });\n  menu.process.addBool('detection rotation', human.config.face.detector, 'rotation', (val) => {\n    human.config.face.detector.rotation = val;\n    human.config.hand.rotation = val;\n  });\n  menu.process.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.process.addButton('process sample images', 'process images', () => detectSampleImages());\n  menu.process.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.process.addChart('FPS', 'FPS');\n\n  menu.models = new Menu(document.body, '', { top: `${document.getElementById('menubar').offsetHeight}px`, left: x[3] });\n  menu.models.addBool('face detect', human.config.face, 'enabled', (val) => human.config.face.enabled = val);\n  menu.models.addBool('face mesh', human.config.face.mesh, 'enabled', (val) => human.config.face.mesh.enabled = val);\n  menu.models.addBool('face iris', human.config.face.iris, 'enabled', (val) => human.config.face.iris.enabled = val);\n  menu.models.addBool('face age', human.config.face.age, 'enabled', (val) => human.config.face.age.enabled = val);\n  menu.models.addBool('face gender', human.config.face.gender, 'enabled', (val) => human.config.face.gender.enabled = val);\n  menu.models.addBool('face emotion', human.config.face.emotion, 'enabled', (val) => human.config.face.emotion.enabled = val);\n  menu.models.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.models.addBool('body pose', human.config.body, 'enabled', (val) => human.config.body.enabled = val);\n  menu.models.addBool('hand pose', human.config.hand, 'enabled', (val) => human.config.hand.enabled = val);\n  menu.models.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.models.addBool('gestures', human.config.gesture, 'enabled', (val) => human.config.gesture.enabled = val);\n  menu.models.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.models.addBool('object detection', human.config.object, 'enabled', (val) => human.config.object.enabled = val);\n  menu.models.addHTML('<hr style=\"border-style: inset; border-color: dimgray\">');\n  menu.models.addBool('face compare', human.config.face.embedding, 'enabled', (val) => {\n    human.config.face.embedding.enabled = val;\n    original = null;\n  });\n\n  document.getElementById('btnDisplay').addEventListener('click', (evt) => menu.display.toggle(evt));\n  document.getElementById('btnImage').addEventListener('click', (evt) => menu.image.toggle(evt));\n  document.getElementById('btnProcess').addEventListener('click', (evt) => menu.process.toggle(evt));\n  document.getElementById('btnModel').addEventListener('click', (evt) => menu.models.toggle(evt));\n  document.getElementById('btnStart').addEventListener('click', () => detectVideo());\n  document.getElementById('play').addEventListener('click', () => detectVideo());\n}\n\nasync function drawWarmup(res) {\n  const canvas = document.getElementById('canvas');\n  canvas.width = res.canvas.width;\n  canvas.height = res.canvas.height;\n  const ctx = canvas.getContext('2d');\n  ctx.drawImage(res.canvas, 0, 0, res.canvas.width, res.canvas.height, 0, 0, canvas.width, canvas.height);\n  await human.draw.all(canvas, res);\n}\n\nasync function main() {\n  log('Demo starting ...');\n  setupMenu();\n  document.getElementById('log').innerText = `Human: version ${human.version}`;\n  if (ui.modelsPreload && !ui.useWorker) {\n    status('loading');\n    await human.load(userConfig); // this is not required, just pre-loads all models\n    const loaded = Object.keys(human.models).filter((a) => human.models[a]);\n    log('Demo loaded models:', loaded);\n  }\n  if (!ui.useWorker) {\n    status('initializing');\n    const res = await human.warmup(userConfig); // this is not required, just pre-warms all models for faster initial inference\n    if (res && res.canvas && ui.drawWarmup) await drawWarmup(res);\n  }\n  status('human: ready');\n  document.getElementById('loader').style.display = 'none';\n  document.getElementById('play').style.display = 'block';\n  log('Demo ready...');\n}\n\nwindow.onload = main;\nwindow.onresize = setupCamera;\n"],
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diff --git a/dist/human.esm-nobundle.js b/dist/human.esm-nobundle.js
index 08e5adb4..0903efce 100644
--- a/dist/human.esm-nobundle.js
+++ b/dist/human.esm-nobundle.js
@@ -5,14 +5,14 @@
   author: <https://github.com/vladmandic>'
   */
 
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dn=[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],fn=[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],mn=[33,133,362,263,1,78,308],gr=dn.map(n=>i1[n]),Tr=fn.map(n=>i1[n]),Pr=mn.map(n=>i1[n]);var x1=te.leftEyeLower0,a1=te.rightEyeLower0,me={leftBounds:[x1[0],x1[x1.length-1]],rightBounds:[a1[0],a1[a1.length-1]]},Oe={count:468,mouth:13,symmetryLine:[13,te.midwayBetweenEyes[0]]},Ot={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},ue={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function Ie(n,e,t,A){for(let r=0;r<s1.length;r++){let{key:c,indices:_}=s1[r],h=te[`${t}${c}`];if(!A||A.includes(c))for(let o=0;o<_.length;o++){let s=_[o];n[h[o]]=[e[s][0],e[s][1],(e[s][2]+n[h[o]][2])/2]}}}var y1=class{constructor(e,t,A){var r,c;this.storedBoxes=[],this.boundingBoxDetector=e,this.meshDetector=t,this.irisModel=A,this.boxSize=((r=e==null?void 0:e.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(t==null?void 0:t.inputs[0].shape[2])||((c=e==null?void 0:e.model)==null?void 0:c.inputs[0].shape[2]),this.irisSize=(A==null?void 0:A.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,t,A,r){let c=be({startPoint:t.startPoint,endPoint:t.endPoint}),_=e.map(i=>[c[0]/this.meshSize*(i[0]-this.meshSize/2),c[1]/this.meshSize*(i[1]-this.meshSize/2),i[2]]),h=A!==0?ke(A,[0,0]):We,o=A!==0?_.map(i=>[...kt(i,h),i[2]]):_,s=A!==0?Wt(r):We,y=[...de({startPoint:t.startPoint,endPoint:t.endPoint}),1];return o.map(i=>[i[0]+he(y,s[0]),i[1]+he(y,s[1]),i[2]])}getLeftToRightEyeDepthDifference(e){let t=e[me.leftBounds[0]][2],A=e[me.rightBounds[0]][2];return t-A}getEyeBox(e,t,A,r,c=!1){let _=je(Se(this.calculateLandmarksBoundingBox([e[A],e[r]]),this.irisEnlarge)),h=be(_),o=q.image.cropAndResize(t,[[_.startPoint[1]/this.meshSize,_.startPoint[0]/this.meshSize,_.endPoint[1]/this.meshSize,_.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return c&&q.ENV.flags.IS_BROWSER&&(o=q.image.flipLeftRight(o)),{box:_,boxSize:h,crop:o}}getEyeCoords(e,t,A,r=!1){let c=[];for(let _=0;_<ue.numCoordinates;_++){let h=e[_*3],o=e[_*3+1],s=e[_*3+2];c.push([(r?1-h/this.irisSize:h/this.irisSize)*A[0]+t.startPoint[0],o/this.irisSize*A[1]+t.startPoint[1],s])}return{rawCoords:c,iris:c.slice(ue.index)}}getAdjustedIrisCoords(e,t,A){let r=e[te[`${A}EyeUpper0`][ue.upperCenter]][2],c=e[te[`${A}EyeLower0`][ue.lowerCenter]][2],_=(r+c)/2;return t.map((h,o)=>{let s=_;return o===2?s=r:o===4&&(s=c),[h[0],h[1],s]})}async predict(e,t){let A=!1,r;if((this.skipped===0||this.skipped>t.face.detector.skipFrames||!t.face.mesh.enabled||!t.videoOptimized)&&(r=await 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h=Nt({startPoint:this.storedBoxes[_].startPoint,endPoint:this.storedBoxes[_].endPoint},r.scaleFactor),o=Se(h),s=je(o),y=this.storedBoxes[_].landmarks.arraySync(),i=this.storedBoxes[_].confidence;this.storedBoxes[_]={...s,confidence:i,landmarks:y}}}r&&r.boxes&&r.boxes.forEach(_=>{_.box.startPoint.dispose(),_.box.endPoint.dispose(),_.landmarks.dispose()});let c=q.tidy(()=>this.storedBoxes.map((_,h)=>{let o=_.confidence,s,y=0,i;if(t.face.detector.rotation&&t.face.mesh.enabled&&q.ENV.flags.IS_BROWSER){let[b,w]=_.landmarks.length>=Oe.count?Oe.symmetryLine:Ot.symmetryLine;y=o1(_.landmarks[b],_.landmarks[w]);let u=de({startPoint:_.startPoint,endPoint:_.endPoint}),M=[u[0]/e.shape[2],u[1]/e.shape[1]],N=q.image.rotateWithOffset(e,y,0,M);i=ke(-y,u),t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},N,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},N,[this.boxSize,this.boxSize]).div(255)}else{i=We;let b=e.clone();t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},b,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},b,[this.boxSize,this.boxSize]).div(255)}if(!t.face.mesh.enabled)return{coords:null,box:_,faceConfidence:null,boxConfidence:_.confidence,confidence:_.confidence,image:s};let[,d,f]=this.meshDetector.predict(s),m=d.dataSync()[0];if(m<t.face.detector.minConfidence)return null;let g=q.reshape(f,[-1,3]).arraySync();if(t.face.iris.enabled){let{box:b,boxSize:w,crop:u}=this.getEyeBox(g,s,me.leftBounds[0],me.leftBounds[1],!0),{box:M,boxSize:N,crop:L}=this.getEyeBox(g,s,me.rightBounds[0],me.rightBounds[1]),ut=this.irisModel.predict(q.concat([u,L])).dataSync(),F0=ut.slice(0,ue.numCoordinates*3),{rawCoords:pt,iris:q0}=this.getEyeCoords(F0,b,w,!0),C0=ut.slice(ue.numCoordinates*3),{rawCoords:bt,iris:Y0}=this.getEyeCoords(C0,M,N),gt=this.getLeftToRightEyeDepthDifference(g);Math.abs(gt)<30?(Ie(g,pt,"left",null),Ie(g,bt,"right",null)):gt<1?Ie(g,pt,"left",["EyeUpper0","EyeLower0"]):Ie(g,bt,"right",["EyeUpper0","EyeLower0"]);let B0=this.getAdjustedIrisCoords(g,q0,"left"),J0=this.getAdjustedIrisCoords(g,Y0,"right");g=g.concat(B0).concat(J0)}let O=this.transformRawCoords(g,_,y,i);_=Se(this.calculateLandmarksBoundingBox(O),1.5);let 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t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c}}};var a0=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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xe.loadGraphModel(n.body.modelPath),G.width=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[2].size),G.height=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[1].size),n.debug&&T(`load model: ${n.body.modelPath.match(/\/(.*)\./)[1]}`)),G}async function _t(n,e){if(!G||!e.body.enabled)return null;let t={width:n.shape[2],height:n.shape[1]},A=xe.image.resizeBilinear(n,[G.width,G.height],!1),r=xe.div(A,[255]);A.dispose();let c;if(e.profile){let s=await xe.profile(()=>G.predict(r));c=s.result.find(y=>y.size===195||y.size===155).dataSync(),s.result.forEach(y=>y.dispose()),D("blazepose",s)}else{let s=await G.predict(r);c=s.find(y=>y.size===195||y.size===155).dataSync(),s.forEach(y=>y.dispose())}r.dispose();let _=[],h=c.length===195?y0:w0,o=5;for(let s=0;s<c.length/o;s++)_.push({id:s,part:h[s],position:{x:Math.trunc(t.width*c[o*s+0]/255),y:Math.trunc(t.height*c[o*s+1]/255),z:Math.trunc(c[o*s+2])+0},score:(100-Math.trunc(100/(1+Math.exp(c[o*s+3]))))/100,presence:(100-Math.trunc(100/(1+Math.exp(c[o*s+4]))))/100});return[{keypoints:_}]}var ht={};U(ht,{load:()=>st,predict:()=>it});var Q=Z();var $,ot=[],Ke=Number.MAX_SAFE_INTEGER,Ue=2.5,Cn=["person","bicycle","car","motorcycle","airplane","bus","train","vehicle","boat","traffic light","fire hydrant","stop sign","parking meter","bench","animal","animal","animal","animal","animal","animal","animal","bear","animal","animal","backpack","umbrella","handbag","tie","suitcase","frisbee","skis","snowboard","sports ball","kite","baseball bat","baseball glove","skateboard","surfboard","tennis racket","bottle","wine glass","cup","fork","knife","spoon","bowl","banana","apple","sandwich","orange","broccoli","carrot","hot dog","pizza","pastry","cake","chair","couch","potted plant","bed","dining 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dn=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],fn=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],mn=[33,133,362,263,1,78,308],gr=dn.map(n=>x1[n]),Tr=fn.map(n=>x1[n]),Pr=mn.map(n=>x1[n]);var a1=te.leftEyeLower0,y1=te.rightEyeLower0,me={leftBounds:[a1[0],a1[a1.length-1]],rightBounds:[y1[0],y1[y1.length-1]]},Ie={count:468,mouth:13,symmetryLine:[13,te.midwayBetweenEyes[0]]},Ot={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},ue={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function Ze(n,e,t,A){for(let r=0;r<i1.length;r++){let{key:c,indices:_}=i1[r],h=te[`${t}${c}`];if(!A||A.includes(c))for(let o=0;o<_.length;o++){let s=_[o];n[h[o]]=[e[s][0],e[s][1],(e[s][2]+n[h[o]][2])/2]}}}var w1=class{constructor(e,t,A){var r,c;this.storedBoxes=[],this.boundingBoxDetector=e,this.meshDetector=t,this.irisModel=A,this.boxSize=((r=e==null?void 0:e.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(t==null?void 0:t.inputs[0].shape[2])||((c=e==null?void 0:e.model)==null?void 0:c.inputs[0].shape[2]),this.irisSize=(A==null?void 0:A.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,t,A,r){let c=ge({startPoint:t.startPoint,endPoint:t.endPoint}),_=e.map(i=>[c[0]/this.meshSize*(i[0]-this.meshSize/2),c[1]/this.meshSize*(i[1]-this.meshSize/2),i[2]]),h=A!==0?Oe(A,[0,0]):ke,o=A!==0?_.map(i=>[...kt(i,h),i[2]]):_,s=A!==0?Wt(r):ke,a=[...de({startPoint:t.startPoint,endPoint:t.endPoint}),1];return o.map(i=>[i[0]+he(a,s[0]),i[1]+he(a,s[1]),i[2]])}getLeftToRightEyeDepthDifference(e){let t=e[me.leftBounds[0]][2],A=e[me.rightBounds[0]][2];return t-A}getEyeBox(e,t,A,r,c=!1){let _=We(je(this.calculateLandmarksBoundingBox([e[A],e[r]]),this.irisEnlarge)),h=ge(_),o=q.image.cropAndResize(t,[[_.startPoint[1]/this.meshSize,_.startPoint[0]/this.meshSize,_.endPoint[1]/this.meshSize,_.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return c&&q.ENV.flags.IS_BROWSER&&(o=q.image.flipLeftRight(o)),{box:_,boxSize:h,crop:o}}getEyeCoords(e,t,A,r=!1){let c=[];for(let _=0;_<ue.numCoordinates;_++){let h=e[_*3],o=e[_*3+1],s=e[_*3+2];c.push([(r?1-h/this.irisSize:h/this.irisSize)*A[0]+t.startPoint[0],o/this.irisSize*A[1]+t.startPoint[1],s])}return{rawCoords:c,iris:c.slice(ue.index)}}getAdjustedIrisCoords(e,t,A){let r=e[te[`${A}EyeUpper0`][ue.upperCenter]][2],c=e[te[`${A}EyeLower0`][ue.lowerCenter]][2],_=(r+c)/2;return t.map((h,o)=>{let s=_;return o===2?s=r:o===4&&(s=c),[h[0],h[1],s]})}async predict(e,t){let A=!1,r;if((this.skipped===0||this.skipped>t.face.detector.skipFrames||!t.face.mesh.enabled||!t.videoOptimized)&&(r=await 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h=Nt({startPoint:this.storedBoxes[_].startPoint,endPoint:this.storedBoxes[_].endPoint},r.scaleFactor),o=je(h),s=We(o),a=this.storedBoxes[_].landmarks.arraySync(),i=this.storedBoxes[_].confidence;this.storedBoxes[_]={...s,confidence:i,landmarks:a}}}r&&r.boxes&&r.boxes.forEach(_=>{_.box.startPoint.dispose(),_.box.endPoint.dispose(),_.landmarks.dispose()});let c=q.tidy(()=>this.storedBoxes.map((_,h)=>{let o=_.confidence,s,a=0,i;if(t.face.detector.rotation&&t.face.mesh.enabled&&q.ENV.flags.IS_BROWSER){let[b,l]=_.landmarks.length>=Ie.count?Ie.symmetryLine:Ot.symmetryLine;a=s1(_.landmarks[b],_.landmarks[l]);let f=de({startPoint:_.startPoint,endPoint:_.endPoint}),R=[f[0]/e.shape[2],f[1]/e.shape[1]],N=q.image.rotateWithOffset(e,a,0,R);i=Oe(-a,f),t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},N,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},N,[this.boxSize,this.boxSize]).div(255)}else{i=ke;let 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t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c}}};var a0=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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y0=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],w0=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var G;async function _t(n){return G||(G=await xe.loadGraphModel(n.body.modelPath),G.width=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[2].size),G.height=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[1].size),n.debug&&T(`load model: ${n.body.modelPath.match(/\/(.*)\./)[1]}`)),G}async function ht(n,e){if(!G||!e.body.enabled)return null;let t={width:n.shape[2],height:n.shape[1]},A=xe.image.resizeBilinear(n,[G.width,G.height],!1),r=xe.div(A,[255]);A.dispose();let c;if(e.profile){let s=await xe.profile(()=>G.predict(r));c=s.result.find(a=>a.size===195||a.size===155).dataSync(),s.result.forEach(a=>a.dispose()),D("blazepose",s)}else{let s=await G.predict(r);c=s.find(a=>a.size===195||a.size===155).dataSync(),s.forEach(a=>a.dispose())}r.dispose();let _=[],h=c.length===195?y0:w0,o=5;for(let 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r,c=[];c.length=0,r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightHip"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftHip"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),c.length===5&&dt(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="leftHip"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftKnee"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftAnkle"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftHeel"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftFoot"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),e1(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="rightHip"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightKnee"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightAnkle"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightHeel"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightFoot"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),e1(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftElbow"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftWrist"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftPalm"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),e1(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightElbow"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightWrist"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightPalm"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),e1(t,c)}}}}async function L0(n,e){if(!e||!n||!(n instanceof HTMLCanvasElement))return;let t=n.getContext("2d");if(!!t){t.lineJoin="round",t.font=l.font;for(let A of e){if(l.drawBoxes&&(t.strokeStyle=l.color,t.fillStyle=l.color,lt(t,A.box[0],A.box[1],A.box[2],A.box[3]),l.drawLabels&&(l.shadowColor&&l.shadowColor!==""&&(t.fillStyle=l.shadowColor,t.fillText("hand",A.box[0]+3,1+A.box[1]+l.lineHeight,A.box[2])),t.fillStyle=l.labelColor,t.fillText("hand",A.box[0]+2,0+A.box[1]+l.lineHeight,A.box[2])),t.stroke()),l.drawPoints&&A.landmarks&&A.landmarks.length>0)for(let r of A.landmarks)t.fillStyle=l.useDepth?`rgba(${127.5+2*r[2]}, ${127.5-2*r[2]}, 255, 0.5)`:l.color,$e(t,r[0],r[1]);if(l.drawPolygons){let r=c=>{if(!!c)for(let _=0;_<c.length;_++)t.lineWidth=l.lineWidth,t.beginPath(),t.strokeStyle=l.useDepth?`rgba(${127.5+2*c[_][2]}, ${127.5-2*c[_][2]}, 255, 0.5)`:l.color,t.moveTo(c[_>0?_-1:0][0],c[_>0?_-1:0][1]),t.lineTo(c[_][0],c[_][1]),t.stroke()};r(A.annotations.indexFinger),r(A.annotations.middleFinger),r(A.annotations.ringFinger),r(A.annotations.pinky),r(A.annotations.thumb)}}}}async function H0(n,e){if(!e||!n||!(n instanceof HTMLCanvasElement))return;let t=n.getContext("2d");if(!!t){t.lineJoin="round",t.font=l.font;for(let A of e)if(l.drawBoxes){if(t.strokeStyle=l.color,t.fillStyle=l.color,lt(t,A.box[0],A.box[1],A.box[2]-A.box[0],A.box[3]-A.box[1]),l.drawLabels){let r=`${Math.round(100*A.score)}% ${A.label}`;l.shadowColor&&l.shadowColor!==""&&(t.fillStyle=l.shadowColor,t.fillText(r,A.box[0]+3,1+A.box[1]+l.lineHeight,A.box[2])),t.fillStyle=l.labelColor,t.fillText(r,A.box[0]+2,0+A.box[1]+l.lineHeight,A.box[2])}t.stroke()}}}async function Kn(n,e){if(!n||!e||!(n instanceof HTMLCanvasElement)||!(e instanceof HTMLCanvasElement))return;let t=n.getContext("2d");t==null||t.drawImage(n,0,0)}async function Un(n,e){!e||!n||n instanceof HTMLCanvasElement&&(Z0(n,e.face),V0(n,e.body),L0(n,e.hand),I0(n,e.gesture),H0(n,e.object))}var E=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Te(...n){let e=t=>t&&typeof t=="object";return n.reduce((t,A)=>(Object.keys(A||{}).forEach(r=>{let c=t[r],_=A[r];Array.isArray(c)&&Array.isArray(_)?t[r]=c.concat(..._):e(c)&&e(_)?t[r]=Te(c,_):t[r]=_}),t),{})}var t1,v,pe,Pe,ve,le,k,n1,ze,r1,Me,A1,c1,_1,X0=class{constructor(e={}){t1.set(this,void 0);v.set(this,void 0);pe.set(this,void 0);Pe.set(this,void 0);ve.set(this,void 0);le.set(this,void 0);k.set(this,(...e)=>{if(!p(this,Pe))return;let t=this.tf.engine().state.numTensors,A=p(this,pe);Ae(this,pe,t);let r=t-A;r!==0&&T(...e,r)});n1.set(this,e=>{if(!p(this,ve))return null;if(!e)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(e instanceof ft.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(t){return"backend not loaded"}return null});ze.set(this,async(e=!1)=>{if(this.config.backend&&this.config.backend!==""&&e||this.tf.getBackend()!==this.config.backend){let t=E();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.config.debug&&T("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&T("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let A=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),r=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&T(`wasm execution: ${A?"SIMD":"no SIMD"} ${r?"multithreaded":"singlethreaded"}`),A||T("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&vt();try{await this.tf.setBackend(this.config.backend)}catch(A){T("error: cannot set backend:",this.config.backend,A)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(T("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let A=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&T(`gl version:${A.getParameter(A.VERSION)} renderer:${A.getParameter(A.RENDERER)}`)}await this.tf.ready(),p(this,v).backend=Math.trunc(E()-t)}});r1.set(this,e=>{if(!e||e.length<300)return{roll:null,yaw:null,pitch:null};let t=(c,_,h,o)=>Math.atan2(o-_,h-c),A=c=>Math.abs(c*180/Math.PI%360);return{roll:t(e[33][0],e[33][1],e[263][0],e[263][1]),yaw:t(e[33][0],e[33][2],e[263][0],e[263][2]),pitch:t(e[10][1],e[10][2],e[152][1],e[152][2])}});Me.set(this,async e=>{var s,y,i,d,f,m,x;let t,A,r,c,_,h=[];this.state="run:face",t=E();let o=await((s=this.models.face)==null?void 0:s.estimateFaces(e,this.config));if(p(this,v).face=Math.trunc(E()-t),!o)return[];for(let g of o){if(p(this,k).call(this,"Get Face"),!g.image||g.image.isDisposedInternal){T("Face object is disposed:",g.image);continue}let O=p(this,r1).call(this,g.mesh);p(this,k).call(this,"Start Age:"),this.config.async?A=this.config.face.age.enabled?u1(g.image,this.config):{}:(this.state="run:age",t=E(),A=this.config.face.age.enabled?await u1(g.image,this.config):{},p(this,v).age=Math.trunc(E()-t)),p(this,k).call(this,"Start Gender:"),this.config.async?r=this.config.face.gender.enabled?v1(g.image,this.config):{}:(this.state="run:gender",t=E(),r=this.config.face.gender.enabled?await v1(g.image,this.config):{},p(this,v).gender=Math.trunc(E()-t)),p(this,k).call(this,"Start Emotion:"),this.config.async?c=this.config.face.emotion.enabled?N1(g.image,this.config):{}:(this.state="run:emotion",t=E(),c=this.config.face.emotion.enabled?await N1(g.image,this.config):{},p(this,v).emotion=Math.trunc(E()-t)),p(this,k).call(this,"End Emotion:"),p(this,k).call(this,"Start Embedding:"),this.config.async?_=this.config.face.embedding.enabled?k1(g,this.config):[]:(this.state="run:embedding",t=E(),_=this.config.face.embedding.enabled?await k1(g,this.config):[],p(this,v).embedding=Math.trunc(E()-t)),p(this,k).call(this,"End Emotion:"),this.config.async&&([A,r,c,_]=await Promise.all([A,r,c,_])),p(this,k).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((y=g==null?void 0:g.annotations)==null?void 0:y.leftEyeIris)&&((i=g==null?void 0:g.annotations)==null?void 0:i.rightEyeIris)&&(delete g.annotations.leftEyeIris,delete g.annotations.rightEyeIris);let I=((d=g.annotations)==null?void 0:d.leftEyeIris)&&((f=g.annotations)==null?void 0:f.rightEyeIris)?11.7*Math.max(Math.abs(g.annotations.leftEyeIris[3][0]-g.annotations.leftEyeIris[1][0]),Math.abs(g.annotations.rightEyeIris[4][1]-g.annotations.rightEyeIris[2][1])):0;h.push({...g,age:A.age,gender:r.gender,genderConfidence:r.confidence,emotion:c,embedding:_,iris:I!==0?Math.trunc(I)/100:0,angle:O,tensor:this.config.face.detector.return?(m=g.image)==null?void 0:m.squeeze():null}),(x=g.image)==null||x.dispose(),p(this,k).call(this,"End Face")}return p(this,k).call(this,"End FaceMesh:"),this.config.async&&(p(this,v).face&&delete p(this,v).face,p(this,v).age&&delete p(this,v).age,p(this,v).gender&&delete p(this,v).gender,p(this,v).emotion&&delete p(this,v).emotion),h});A1.set(this,async()=>{let e=(r,c="application/octet-stream")=>fetch(`data:${c};base64,${r}`).then(_=>_.blob()),t,A;switch(this.config.warmup){case"face":t=await e(Ge);break;case"full":t=await e(Qe);break;default:t=null}if(t){let r=await createImageBitmap(t);A=await this.detect(r,this.config),r.close()}return A});c1.set(this,async()=>new Promise(e=>{let t,A=0;switch(this.config.warmup){case"face":A=256,t="data:image/jpeg;base64,"+Ge;break;case"full":case"body":A=1200,t="data:image/jpeg;base64,"+Qe;break;default:t=null}let r=new Image;r.onload=async()=>{let c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(A,A):document.createElement("canvas");c.width=r.naturalWidth,c.height=r.naturalHeight;let _=c.getContext("2d");_==null||_.drawImage(r,0,0);let h=await this.detect(c,this.config);e(h)},t?r.src=t:e(null)}));_1.set(this,async()=>{let e=_=>Buffer.from(_,"base64"),t=this.config.warmup==="face"?e(Ge):e(Qe),A=ft.node.decodeJpeg(t),r=A.expandDims(0);this.tf.dispose(A);let c=await this.detect(r,this.config);return this.tf.dispose(r),c});this.tf=ft,this.draw=wt,Ae(this,t1,at),this.version=yt,this.config=Te(j,e),this.state="idle",Ae(this,pe,0),Ae(this,Pe,!1),Ae(this,ve,!1),Ae(this,le,!0),Ae(this,v,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=t=>xt(t,this.config),this.classes={facemesh:mt,age:f1,gender:p1,emotion:z1,body:this.config.body.modelPath.includes("posenet")?B1:At,hand:$1,nanodet:ht},this.sysinfo=Pt()}profileData(){return this.config.profile?d1:{}}simmilarity(e,t){return this.config.face.embedding.enabled?j1(e,t):0}enhance(e){return W1(e)}match(e,t,A=0){return Vt(e,t,A)}async load(e={}){this.state="load";let t=E();e&&(this.config=Te(this.config,e)),p(this,le)&&(this.config.debug&&T(`version: ${this.version}`),this.config.debug&&T(`tfjs version: ${this.tf.version_core}`),this.config.debug&&T("platform:",this.sysinfo.platform),this.config.debug&&T("agent:",this.sysinfo.agent),await p(this,ze).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&T("configuration:",this.config),this.config.debug&&T("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?mt.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?m1(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?P1(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?E1(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?S1(this.config):null),this.models.handpose||(this.config.hand.enabled?rt(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?K1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?ct(this.config):null),this.models.nanodet||(this.config.object.enabled?st(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await mt.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await m1(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await P1(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await E1(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await S1(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await rt(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await K1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await ct(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await st(this.config))),p(this,le)&&(this.config.debug&&T("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),Ae(this,le,!1));let A=Math.trunc(E()-t);A>(p(this,v).load||0)&&(p(this,v).load=A)}async detect(e,t={}){return new Promise(async A=>{var f,m,x,g;this.state="config";let r;this.config=Te(this.config,t),this.state="check";let c=p(this,n1).call(this,e);c&&(T(c,e),A({error:c}));let _=E();await p(this,ze).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),p(this,k).call(this,"Start Scope:"),r=E();let h=xt(e,this.config);if(!h||!h.tensor){T("could not convert input to tensor"),A({error:"could not convert input to tensor"});return}p(this,v).image=Math.trunc(E()-r),p(this,k).call(this,"Get Image:");let o,s,y,i;this.config.async?(y=this.config.face.enabled?p(this,Me).call(this,h.tensor):[],p(this,v).face&&delete p(this,v).face):(this.state="run:face",r=E(),y=this.config.face.enabled?await p(this,Me).call(this,h.tensor):[],p(this,v).face=Math.trunc(E()-r)),p(this,k).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?(f=this.models.posenet)==null?void 0:f.estimatePoses(h.tensor,this.config):[]:o=this.config.body.enabled?_t(h.tensor,this.config):[],p(this,v).body&&delete p(this,v).body):(this.state="run:body",r=E(),this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?await((m=this.models.posenet)==null?void 0:m.estimatePoses(h.tensor,this.config)):[]:o=this.config.body.enabled?await _t(h.tensor,this.config):[],p(this,v).body=Math.trunc(E()-r)),p(this,k).call(this,"End Body:"),p(this,k).call(this,"Start Hand:"),this.config.async?(s=this.config.hand.enabled?(x=this.models.handpose)==null?void 0:x.estimateHands(h.tensor,this.config):[],p(this,v).hand&&delete p(this,v).hand):(this.state="run:hand",r=E(),s=this.config.hand.enabled?await((g=this.models.handpose)==null?void 0:g.estimateHands(h.tensor,this.config)):[],p(this,v).hand=Math.trunc(E()-r)),p(this,k).call(this,"End Hand:"),p(this,k).call(this,"Start Object:"),this.config.async?(i=this.config.object.enabled?it(h.tensor,this.config):[],p(this,v).object&&delete p(this,v).object):(this.state="run:object",r=E(),i=this.config.object.enabled?await it(h.tensor,this.config):[],p(this,v).object=Math.trunc(E()-r)),p(this,k).call(this,"End Object:"),this.config.async&&([y,o,s,i]=await Promise.all([y,o,s,i])),h.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),p(this,k).call(this,"End Scope:");let d=[];this.config.gesture.enabled&&(r=E(),d=[...d0(y),...l0(o),...m0(s),...f0(y)],this.config.async?p(this,v).gesture&&delete p(this,v).gesture:p(this,v).gesture=Math.trunc(E()-r)),p(this,v).total=Math.trunc(E()-_),this.state="idle",A({face:y,body:o,hand:s,gesture:d,object:i,performance:p(this,v),canvas:h.canvas})})}async warmup(e={}){let t=E();e&&(this.config=Te(this.config,e));let A=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await p(this,A1).call(this):typeof Image!="undefined"?r=await p(this,c1).call(this):r=await p(this,_1).call(this),this.config.videoOptimized=A;let c=E();return this.config.debug&&T("Warmup",this.config.warmup,Math.round(c-t),"ms",r),r}};t1=new WeakMap,v=new WeakMap,pe=new WeakMap,Pe=new WeakMap,ve=new WeakMap,le=new WeakMap,k=new WeakMap,n1=new WeakMap,ze=new WeakMap,r1=new WeakMap,Me=new WeakMap,A1=new WeakMap,c1=new WeakMap,_1=new WeakMap;export{X0 as Human,X0 as default};
+2Q==`;var yt={};U(yt,{author:()=>R0,browser:()=>v0,bugs:()=>M0,default:()=>Cn,description:()=>b0,devDependencies:()=>O0,engines:()=>S0,homepage:()=>E0,keywords:()=>k0,license:()=>N0,main:()=>T0,module:()=>P0,name:()=>p0,repository:()=>j0,scripts:()=>W0,sideEffects:()=>g0,types:()=>z0,version:()=>wt});var p0="@vladmandic/human",wt="1.1.8",b0="Human: AI-powered 3D Face Detection, Face Embedding & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition",g0=!1,T0="dist/human.node.js",P0="dist/human.esm.js",v0="dist/human.esm.js",z0="types/src/human.d.ts",R0="Vladimir Mandic <mandic00@live.com>",M0={url:"https://github.com/vladmandic/human/issues"},E0="https://vladmandic.github.io/human/demo/index.html",N0="MIT",S0={node:">=12.0.0"},j0={type:"git",url:"git+https://github.com/vladmandic/human.git"},W0={start:"node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation demo/node.js",dev:"node 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start"},k0=["tensorflowjs","face-detection","face-geometry","face-embedding","face-recognition","body-tracking","hand-tracking","iris-tracking","age-estimation","emotion-detection","gender-prediction","gesture-recognition","blazeface","blazepose","nanodet"],O0={"@microsoft/api-extractor":"^7.13.2","@tensorflow/tfjs":"^3.3.0","@tensorflow/tfjs-backend-cpu":"^3.3.0","@tensorflow/tfjs-backend-wasm":"^3.3.0","@tensorflow/tfjs-backend-webgl":"^3.3.0","@tensorflow/tfjs-converter":"^3.3.0","@tensorflow/tfjs-core":"^3.3.0","@tensorflow/tfjs-data":"^3.3.0","@tensorflow/tfjs-layers":"^3.3.0","@tensorflow/tfjs-node":"^3.3.0","@tensorflow/tfjs-node-gpu":"^3.3.0","@types/node":"^14.14.35","@typescript-eslint/eslint-plugin":"^4.18.0","@typescript-eslint/parser":"^4.18.0","@vladmandic/pilogger":"^0.2.14",chokidar:"^3.5.1",dayjs:"^1.10.4",esbuild:"^0.9.3",eslint:"^7.22.0","eslint-config-airbnb-base":"^14.2.1","eslint-plugin-import":"^2.22.1","eslint-plugin-json":"^2.1.2","eslint-plugin-node":"^11.1.0","eslint-plugin-promise":"^4.3.1",rimraf:"^3.0.2",seedrandom:"^3.0.5","simple-git":"^2.37.0",tslib:"^2.1.0",typedoc:"^0.20.32",typescript:"^4.2.3"},Cn={name:p0,version:wt,description:b0,sideEffects:g0,main:T0,module:P0,browser:v0,types:z0,author:R0,bugs:M0,homepage:E0,license:N0,engines:S0,repository:j0,scripts:W0,keywords:k0,devDependencies:O0};var lt={};U(lt,{all:()=>Un,body:()=>L0,canvas:()=>Kn,drawOptions:()=>w,face:()=>Z0,gesture:()=>I0,hand:()=>V0,object:()=>H0});var w={color:"rgba(173, 216, 230, 0.3)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",font:'small-caps 16px "Segoe UI"',lineHeight:20,lineWidth:6,pointSize:2,roundRect:28,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawPolygons:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,bufferedOutput:!1,useRawBoxes:!1};function e1(n,e,t,A=null){n.fillStyle=w.useDepth&&A?`rgba(${127.5+2*(A||0)}, ${127.5-2*(A||0)}, 255, 0.3)`:w.color,n.beginPath(),n.arc(e,t,w.pointSize,0,2*Math.PI),n.fill()}function pe(n,e,t,A,r){if(n.beginPath(),w.useCurves){let c=(e+e+A)/2,_=(t+t+r)/2;n.ellipse(c,_,A/2,r/2,0,0,2*Math.PI)}else n.lineWidth=w.lineWidth,n.moveTo(e+w.roundRect,t),n.lineTo(e+A-w.roundRect,t),n.quadraticCurveTo(e+A,t,e+A,t+w.roundRect),n.lineTo(e+A,t+r-w.roundRect),n.quadraticCurveTo(e+A,t+r,e+A-w.roundRect,t+r),n.lineTo(e+w.roundRect,t+r),n.quadraticCurveTo(e,t+r,e,t+r-w.roundRect),n.lineTo(e,t+w.roundRect),n.quadraticCurveTo(e,t,e+w.roundRect,t),n.closePath();n.stroke()}function dt(n,e=[]){if(!(e===void 0||e.length===0)){n.beginPath(),n.moveTo(e[0][0],e[0][1]);for(let t of e)n.strokeStyle=w.useDepth&&t[2]?`rgba(${127.5+2*t[2]}, ${127.5-2*t[2]}, 255, 0.3)`:w.color,n.fillStyle=w.useDepth&&t[2]?`rgba(${127.5+2*t[2]}, ${127.5-2*t[2]}, 255, 0.3)`:w.color,n.lineTo(t[0],parseInt(t[1]));n.stroke(),w.fillPolygons&&(n.closePath(),n.fill())}}function t1(n,e=[]){if(!(e===void 0||e.length===0)){if(!w.useCurves||e.length<=2){dt(n,e);return}n.moveTo(e[0][0],e[0][1]);for(let t=0;t<e.length-2;t++){let A=(e[t][0]+e[t+1][0])/2,r=(e[t][1]+e[t+1][1])/2;n.quadraticCurveTo(e[t][0],e[t][1],A,r)}n.quadraticCurveTo(e[e.length-2][0],e[e.length-2][1],e[e.length-1][0],e[e.length-1][1]),n.stroke(),w.fillPolygons&&(n.closePath(),n.fill())}}async function I0(n,e){if(!e||!n||!(n instanceof HTMLCanvasElement))return;let t=n.getContext("2d");if(!t)return;t.font=w.font,t.fillStyle=w.color;let A=1;for(let r=0;r<e.length;r++){let c=[],_=[];if([c,_]=Object.entries(e[r]),_.length>1&&_[1].length>0){let h=c[1]>0?`#${c[1]}`:"",o=`${c[0]} ${h}: ${_[1]}`;w.shadowColor&&w.shadowColor!==""&&(t.fillStyle=w.shadowColor,t.fillText(o,8,2+A*w.lineHeight)),t.fillStyle=w.labelColor,t.fillText(o,6,0+A*w.lineHeight),A+=1}}}async function Z0(n,e){if(!e||!n||!(n instanceof HTMLCanvasElement))return;let t=n.getContext("2d");if(!!t)for(let A of e){t.font=w.font,t.strokeStyle=w.color,t.fillStyle=w.color,w.drawBoxes&&(w.useRawBoxes?pe(t,n.width*A.boxRaw[0],n.height*A.boxRaw[1],n.width*A.boxRaw[2],n.height*A.boxRaw[3]):pe(t,A.box[0],A.box[1],A.box[2],A.box[3]));let r=[];if(r.push(`face confidence: ${Math.trunc(100*A.confidence)}%`),A.genderConfidence&&r.push(`${A.gender||""} ${Math.trunc(100*A.genderConfidence)}% confident`),A.age&&r.push(`age: ${A.age||""}`),A.iris&&r.push(`iris distance: ${A.iris}`),A.emotion&&A.emotion.length>0){let c=A.emotion.map(_=>`${Math.trunc(100*_.score)}% ${_.emotion}`);r.push(c.join(" "))}A.angle&&A.angle.roll&&r.push(`roll: ${Math.trunc(100*A.angle.roll)/100} yaw:${Math.trunc(100*A.angle.yaw)/100} pitch:${Math.trunc(100*A.angle.pitch)/100}`),r.length===0&&r.push("face"),t.fillStyle=w.color;for(let c=r.length-1;c>=0;c--){let _=Math.max(A.box[0],0),h=c*w.lineHeight+A.box[1];w.shadowColor&&w.shadowColor!==""&&(t.fillStyle=w.shadowColor,t.fillText(r[c],_+5,h+16)),t.fillStyle=w.labelColor,t.fillText(r[c],_+4,h+15)}if(t.lineWidth=1,A.mesh&&A.mesh.length>0){if(w.drawPoints)for(let c of A.mesh)e1(t,c[0],c[1],c[2]);if(w.drawPolygons){t.lineWidth=1;for(let c=0;c<ye.length/3;c++){let _=[ye[c*3+0],ye[c*3+1],ye[c*3+2]].map(h=>A.mesh[h]);dt(t,_)}if(A.annotations&&A.annotations.leftEyeIris){t.strokeStyle=w.useDepth?"rgba(255, 200, 255, 0.3)":w.color,t.beginPath();let c=Math.abs(A.annotations.leftEyeIris[3][0]-A.annotations.leftEyeIris[1][0])/2,_=Math.abs(A.annotations.leftEyeIris[4][1]-A.annotations.leftEyeIris[2][1])/2;t.ellipse(A.annotations.leftEyeIris[0][0],A.annotations.leftEyeIris[0][1],c,_,0,0,2*Math.PI),t.stroke(),w.fillPolygons&&(t.fillStyle=w.useDepth?"rgba(255, 255, 200, 0.3)":w.color,t.fill())}if(A.annotations&&A.annotations.rightEyeIris){t.strokeStyle=w.useDepth?"rgba(255, 200, 255, 0.3)":w.color,t.beginPath();let c=Math.abs(A.annotations.rightEyeIris[3][0]-A.annotations.rightEyeIris[1][0])/2,_=Math.abs(A.annotations.rightEyeIris[4][1]-A.annotations.rightEyeIris[2][1])/2;t.ellipse(A.annotations.rightEyeIris[0][0],A.annotations.rightEyeIris[0][1],c,_,0,0,2*Math.PI),t.stroke(),w.fillPolygons&&(t.fillStyle=w.useDepth?"rgba(255, 255, 200, 0.3)":w.color,t.fill())}}}}}var ae=[];async function L0(n,e){if(!e||!n||!(n instanceof HTMLCanvasElement))return;let t=n.getContext("2d");if(!!t){t.lineJoin="round";for(let A=0;A<e.length;A++){if(!ae[A]&&w.bufferedOutput&&(ae[A]={...e[A]}),t.strokeStyle=w.color,t.lineWidth=w.lineWidth,w.drawPoints)for(let r=0;r<e[A].keypoints.length;r++)t.fillStyle=w.useDepth&&e[A].keypoints[r].position.z?`rgba(${127.5+2*e[A].keypoints[r].position.z}, ${127.5-2*e[A].keypoints[r].position.z}, 255, 0.5)`:w.color,w.bufferedOutput?(ae[A].keypoints[r][0]=(ae[A].keypoints[r][0]+e[A].keypoints[r].position.x)/2,ae[A].keypoints[r][1]=(ae[A].keypoints[r][1]+e[A].keypoints[r].position.y)/2,e1(t,ae[A].keypoints[r][0],ae[A].keypoints[r][1])):e1(t,e[A].keypoints[r].position.x,e[A].keypoints[r].position.y);if(w.drawLabels){t.font=w.font;for(let r of e[A].keypoints)t.fillStyle=w.useDepth&&r.position.z?`rgba(${127.5+2*r.position.z}, ${127.5-2*r.position.z}, 255, 0.5)`:w.color,t.fillText(`${r.part}`,r.position.x+4,r.position.y+4)}if(w.drawPolygons){let r,c=[];c.length=0,r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightHip"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftHip"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),c.length===5&&dt(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="leftHip"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftKnee"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftAnkle"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftHeel"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftFoot"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),t1(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="rightHip"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightKnee"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightAnkle"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightHeel"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightFoot"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),t1(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftElbow"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftWrist"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftPalm"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),t1(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightElbow"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightWrist"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightPalm"),r&&r.score>j.body.scoreThreshold&&c.push([r.position.x,r.position.y]),t1(t,c)}}}}async 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backend:",this.config.backend,A)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(T("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let A=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&T(`gl version:${A.getParameter(A.VERSION)} renderer:${A.getParameter(A.RENDERER)}`)}await this.tf.ready(),p(this,v).backend=Math.trunc(E()-t)}});A1.set(this,e=>{if(!e||e.length<300)return{roll:null,yaw:null,pitch:null};let t=(c,_,h,o)=>Math.atan2(o-_,h-c),A=c=>Math.abs(c*180/Math.PI%360);return{roll:t(e[33][0],e[33][1],e[263][0],e[263][1]),yaw:t(e[33][0],e[33][2],e[263][0],e[263][2]),pitch:t(e[10][1],e[10][2],e[152][1],e[152][2])}});Me.set(this,async e=>{var s,a,i,d,u,m,x;let t,A,r,c,_,h=[];this.state="run:face",t=E();let o=await((s=this.models.face)==null?void 0:s.estimateFaces(e,this.config));if(p(this,v).face=Math.trunc(E()-t),!o)return[];for(let g of o){if(p(this,O).call(this,"Get Face"),!g.image||g.image.isDisposedInternal){T("Face object is disposed:",g.image);continue}let W=p(this,A1).call(this,g.mesh);p(this,O).call(this,"Start Age:"),this.config.async?A=this.config.face.age.enabled?p1(g.image,this.config):{}:(this.state="run:age",t=E(),A=this.config.face.age.enabled?await p1(g.image,this.config):{},p(this,v).age=Math.trunc(E()-t)),p(this,O).call(this,"Start Gender:"),this.config.async?r=this.config.face.gender.enabled?z1(g.image,this.config):{}:(this.state="run:gender",t=E(),r=this.config.face.gender.enabled?await z1(g.image,this.config):{},p(this,v).gender=Math.trunc(E()-t)),p(this,O).call(this,"Start Emotion:"),this.config.async?c=this.config.face.emotion.enabled?S1(g.image,this.config):{}:(this.state="run:emotion",t=E(),c=this.config.face.emotion.enabled?await S1(g.image,this.config):{},p(this,v).emotion=Math.trunc(E()-t)),p(this,O).call(this,"End Emotion:"),p(this,O).call(this,"Start Embedding:"),this.config.async?_=this.config.face.embedding.enabled?O1(g,this.config):[]:(this.state="run:embedding",t=E(),_=this.config.face.embedding.enabled?await O1(g,this.config):[],p(this,v).embedding=Math.trunc(E()-t)),p(this,O).call(this,"End Emotion:"),this.config.async&&([A,r,c,_]=await Promise.all([A,r,c,_])),p(this,O).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((a=g==null?void 0:g.annotations)==null?void 0:a.leftEyeIris)&&((i=g==null?void 0:g.annotations)==null?void 0:i.rightEyeIris)&&(delete g.annotations.leftEyeIris,delete g.annotations.rightEyeIris);let I=((d=g.annotations)==null?void 0:d.leftEyeIris)&&((u=g.annotations)==null?void 0:u.rightEyeIris)?11.7*Math.max(Math.abs(g.annotations.leftEyeIris[3][0]-g.annotations.leftEyeIris[1][0]),Math.abs(g.annotations.rightEyeIris[4][1]-g.annotations.rightEyeIris[2][1])):0;h.push({...g,age:A.age,gender:r.gender,genderConfidence:r.confidence,emotion:c,embedding:_,iris:I!==0?Math.trunc(I)/100:0,angle:W,tensor:this.config.face.detector.return?(m=g.image)==null?void 0:m.squeeze():null}),(x=g.image)==null||x.dispose(),p(this,O).call(this,"End Face")}return p(this,O).call(this,"End FaceMesh:"),this.config.async&&(p(this,v).face&&delete p(this,v).face,p(this,v).age&&delete p(this,v).age,p(this,v).gender&&delete p(this,v).gender,p(this,v).emotion&&delete p(this,v).emotion),h});c1.set(this,async()=>{let e=(r,c="application/octet-stream")=>fetch(`data:${c};base64,${r}`).then(_=>_.blob()),t,A;switch(this.config.warmup){case"face":t=await e(Qe);break;case"full":t=await e($e);break;default:t=null}if(t){let r=await createImageBitmap(t);A=await this.detect(r,this.config),r.close()}return A});_1.set(this,async()=>new Promise(e=>{let t,A=0;switch(this.config.warmup){case"face":A=256,t="data:image/jpeg;base64,"+Qe;break;case"full":case"body":A=1200,t="data:image/jpeg;base64,"+$e;break;default:t=null}let r=new Image;r.onload=async()=>{let c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(A,A):document.createElement("canvas");c.width=r.naturalWidth,c.height=r.naturalHeight;let _=c.getContext("2d");_==null||_.drawImage(r,0,0);let h=await this.detect(c,this.config);e(h)},t?r.src=t:e(null)}));h1.set(this,async()=>{let e=_=>Buffer.from(_,"base64"),t=this.config.warmup==="face"?e(Qe):e($e),A=ft.node.decodeJpeg(t),r=A.expandDims(0);this.tf.dispose(A);let c=await this.detect(r,this.config);return this.tf.dispose(r),c});this.tf=ft,this.draw=lt,Ae(this,n1,yt),this.version=wt,this.config=Pe(j,e),this.state="idle",Ae(this,be,0),Ae(this,ve,!1),Ae(this,ze,!1),Ae(this,le,!0),Ae(this,v,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=t=>at(t,this.config),this.classes={facemesh:mt,age:m1,gender:b1,emotion:R1,body:this.config.body.modelPath.includes("posenet")?C1:ct,hand:et,nanodet:ot},this.sysinfo=Pt()}profileData(){return this.config.profile?f1:{}}simmilarity(e,t){return this.config.face.embedding.enabled?W1(e,t):0}enhance(e){return k1(e)}match(e,t,A=0){return Lt(e,t,A)}async load(e={}){this.state="load";let t=E();e&&(this.config=Pe(this.config,e)),p(this,le)&&(this.config.debug&&T(`version: ${this.version}`),this.config.debug&&T(`tfjs version: ${this.tf.version_core}`),this.config.debug&&T("platform:",this.sysinfo.platform),this.config.debug&&T("agent:",this.sysinfo.agent),await p(this,Re).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&T("configuration:",this.config),this.config.debug&&T("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?mt.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?u1(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?v1(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?N1(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?j1(this.config):null),this.models.handpose||(this.config.hand.enabled?At(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?U1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?_t(this.config):null),this.models.nanodet||(this.config.object.enabled?it(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await mt.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await u1(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await v1(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await N1(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await j1(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await At(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await U1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await _t(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await it(this.config))),p(this,le)&&(this.config.debug&&T("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),Ae(this,le,!1));let A=Math.trunc(E()-t);A>(p(this,v).load||0)&&(p(this,v).load=A)}async detect(e,t={}){return new Promise(async A=>{var m,x,g,W;this.state="config";let r;this.config=Pe(this.config,t),this.state="check";let c=p(this,r1).call(this,e);c&&(T(c,e),A({error:c}));let _=E();await p(this,Re).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),p(this,O).call(this,"Start Scope:"),r=E();let h=at(e,this.config);if(!h||!h.tensor){T("could not convert input to tensor"),A({error:"could not convert input to tensor"});return}p(this,v).image=Math.trunc(E()-r),p(this,O).call(this,"Get Image:");let o,s,a,i;this.config.async?(a=this.config.face.enabled?p(this,Me).call(this,h.tensor):[],p(this,v).face&&delete p(this,v).face):(this.state="run:face",r=E(),a=this.config.face.enabled?await p(this,Me).call(this,h.tensor):[],p(this,v).face=Math.trunc(E()-r)),p(this,O).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?(m=this.models.posenet)==null?void 0:m.estimatePoses(h.tensor,this.config):[]:o=this.config.body.enabled?ht(h.tensor,this.config):[],p(this,v).body&&delete p(this,v).body):(this.state="run:body",r=E(),this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?await((x=this.models.posenet)==null?void 0:x.estimatePoses(h.tensor,this.config)):[]:o=this.config.body.enabled?await ht(h.tensor,this.config):[],p(this,v).body=Math.trunc(E()-r)),p(this,O).call(this,"End Body:"),p(this,O).call(this,"Start Hand:"),this.config.async?(s=this.config.hand.enabled?(g=this.models.handpose)==null?void 0:g.estimateHands(h.tensor,this.config):[],p(this,v).hand&&delete p(this,v).hand):(this.state="run:hand",r=E(),s=this.config.hand.enabled?await((W=this.models.handpose)==null?void 0:W.estimateHands(h.tensor,this.config)):[],p(this,v).hand=Math.trunc(E()-r)),p(this,O).call(this,"End Hand:"),p(this,O).call(this,"Start Object:"),this.config.async?(i=this.config.object.enabled?xt(h.tensor,this.config):[],p(this,v).object&&delete p(this,v).object):(this.state="run:object",r=E(),i=this.config.object.enabled?await xt(h.tensor,this.config):[],p(this,v).object=Math.trunc(E()-r)),p(this,O).call(this,"End Object:"),this.config.async&&([a,o,s,i]=await Promise.all([a,o,s,i])),h.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),p(this,O).call(this,"End Scope:");let d=[];this.config.gesture.enabled&&(r=E(),d=[...d0(a),...l0(o),...m0(s),...f0(a)],this.config.async?p(this,v).gesture&&delete p(this,v).gesture:p(this,v).gesture=Math.trunc(E()-r)),p(this,v).total=Math.trunc(E()-_),this.state="idle";let u={face:a,body:o,hand:s,gesture:d,object:i,performance:p(this,v),canvas:h.canvas};A(u)})}async warmup(e={}){let t=E();e&&(this.config=Pe(this.config,e));let A=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await p(this,c1).call(this):typeof Image!="undefined"?r=await p(this,_1).call(this):r=await p(this,h1).call(this),this.config.videoOptimized=A;let c=E();return this.config.debug&&T("Warmup",this.config.warmup,Math.round(c-t),"ms",r),r}};n1=new WeakMap,v=new WeakMap,be=new WeakMap,ve=new WeakMap,ze=new WeakMap,le=new WeakMap,O=new WeakMap,r1=new WeakMap,Re=new WeakMap,A1=new WeakMap,Me=new WeakMap,c1=new WeakMap,_1=new WeakMap,h1=new WeakMap;export{X0 as Human,X0 as default};
 //# sourceMappingURL=human.esm-nobundle.js.map
diff --git a/dist/human.esm-nobundle.js.map b/dist/human.esm-nobundle.js.map
index 2af7c7bd..f5c75275 100644
--- a/dist/human.esm-nobundle.js.map
+++ b/dist/human.esm-nobundle.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["../src/tfjs/tf-browser.ts", "../src/blazeface/facemesh.ts", "../src/posenet/keypoints.ts", "../src/log.ts", "../src/sysinfo.ts", "../src/human.ts", "../src/tfjs/backend.ts", "../src/blazeface/blazeface.ts", "../src/blazeface/facepipeline.ts", "../src/blazeface/box.ts", "../src/blazeface/util.ts", "../src/blazeface/coords.ts", "../src/age/age.ts", "../src/profile.ts", "../src/gender/gender.ts", "../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/decodePose.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/handdetector.ts", "../src/handpose/box.ts", "../src/handpose/handpipeline.ts", "../src/handpose/util.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/nanodet/nanodet.ts", "../src/gesture/gesture.ts", "../src/image.ts", "../src/imagefx.js", "../config.ts", "../src/sample.ts", "../src/draw.ts"],
-  "sourcesContent": ["// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - prediction.box.startPoint[0],\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - prediction.box.startPoint[1],\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0] / input.shape[2]),\n        Math.max(0, prediction.box.startPoint[1] / input.shape[1]),\n        Math.min(input.shape[1], (prediction.box.endPoint[0]) - prediction.box.startPoint[0]) / input.shape[2],\n        Math.min(input.shape[2], (prediction.box.endPoint[1]) - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        mesh,\n        boxRaw,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      resolve({ face: faceRes, body: bodyRes, hand: handRes, gesture: gestureRes, object: objectRes, performance: this.#perf, canvas: process.canvas });\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 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0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - prediction.box.topLeft[0],\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - prediction.box.topLeft[1],\n      ] : 0;\n      hands.push({ confidence: prediction.confidence, box, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            boxRaw[0] * outputShape[0],\n            boxRaw[1] * outputShape[1],\n            boxRaw[2] * outputShape[0],\n            boxRaw[3] * outputShape[1],\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n      // rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2] - h.box[0], h.box[3] - h.box[1]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
-  "mappings": 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+  "sourcesContent": ["// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    boxRaw: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.#perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 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0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: prediction.confidence, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            Math.max(0, (boxRaw[0] * outputShape[0])),\n            Math.max(0, (boxRaw[1] * outputShape[1])),\n            Math.min(1, (boxRaw[2] * outputShape[0]) - (boxRaw[0] * outputShape[0])),\n            Math.min(1, (boxRaw[3] * outputShape[1]) - (boxRaw[1] * outputShape[1])),\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
+  "mappings": 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diff --git a/dist/human.esm.js b/dist/human.esm.js
index 744d1d08..02677464 100644
--- a/dist/human.esm.js
+++ b/dist/human.esm.js
@@ -5,31 +5,31 @@
   author: <https://github.com/vladmandic>'
   */
 
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r=++this.pendingBackendInitId,a=n.then(s=>r<this.pendingBackendInitId?!1:(this.registry[e]=s,this.pendingBackendInit=null,!0)).catch(s=>(r<this.pendingBackendInitId||(this.pendingBackendInit=null,console.warn(`Initialization of backend ${e} failed`),console.warn(s.stack||s.message)),!1));return this.pendingBackendInit=a,{success:a,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return console.warn(`Initialization of backend ${e} failed`),console.warn(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t],{success:r,asyncInit:a}=this.initializeBackend(n);if(a||r)return{name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),r=n.backend,a=this.readSync(t),s=r.refCount(t);r.disposeData(t,!0),n.backend=e,e.move(t,a,n.shape,n.dtype,s),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");n=e}let r;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(r),()=>(r=t(),r instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),r))}scopedRun(e,t,n){e();try{let r=n();return t(),r}catch(r){throw t(),r}}nextTensorId(){return Mu.nextTensorId++}nextVariableId(){return Mu.nextVariableId++}clone(e){let t=$.runKernel(Ns,{x:e}),n={x:e},r=s=>({x:()=>{let i="float32",o={x:s},l={dtype:i};return $.runKernel(ds,o,l)}}),a=[];return this.addTapeNode(this.state.activeScope.name,n,[t],r,a,{}),t}runKernel(e,t,n){if(nd(e,this.backendName)==null)throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let r=this.backend.numDataIds(),a=0;n.forEach(o=>{a+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-t-a-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],r=this.isTapeOn(),a=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=yf(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(yf(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let A=nd(p,this.backendName);F(A!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),i=()=>{let y=this.backend.numDataIds();o=A.kernelFunc({inputs:f,attrs:m,backend:this.backend});let g=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,y,g);let w=g.map(b=>{if(b.rank!=null)return b;let{dataId:_,shape:x,dtype:I}=b;return this.makeTensorFromDataId(_,x,I)});if(r){let b=this.getTensorsForGradient(p,f,w);n=this.saveTensorsForBackwardMode(b)}return w}}else{let{forwardFunc:p}=e,f=m=>{!r||(n=m.map(A=>this.keep(this.clone(A))))};i=()=>{let m=this.backend.numDataIds();o=this.tidy(()=>p(this.backend,f));let A=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,A),A}}let{inputs:u,attrs:c}=e,h=yf(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,u,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,u,t,h,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(p=>u[p]!=null?u[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let r=uf(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(F(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let o=n.filter((l,u)=>s[u]);return i.concat(o)}return[]}makeTensor(e,t,n,r){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;let a=e;n==="string"&&ka(e[0])&&(a=e.map(o=>Tu(o)));let s=r.write(a,t,n),i=new je(t,n,s,this.nextTensorId());if(this.trackTensor(i,r),n==="string"){let o=this.state.tensorInfo.get(s),l=Xg(a);this.state.numBytes+=l-o.bytes,o.bytes=l}return i}makeTensorFromDataId(e,t,n,r){n=n||"float32";let a=new je(t,n,e,this.nextTensorId());return this.trackTensor(a,r),a}makeVariable(e,t=!0,n,r){n=n||this.nextVariableId().toString(),r!=null&&r!==e.dtype&&(e=e.cast(r));let a=new Fu(e,t,n,this.nextTensorId());if(this.state.registeredVariables[a.name]!=null)throw new Error(`Variable with name ${a.name} was already registered`);return this.state.registeredVariables[a.name]=a,this.incRef(a,this.backend),a}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*tf(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 Fu||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*tf(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,a,s){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:a},o=uf(e);o!=null&&(r=o.gradFunc),r!=null&&(i.gradient=l=>(l=l.map((u,c)=>{if(u==null){let h=n[c],d=vh(h.size,h.dtype);return this.makeTensor(d,h.shape,h.dtype)}return u}),r(l.length>1?l:l[0],a,s))),this.state.activeTape.push(i)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=hf(e),n=new Set(t.map(a=>a.id));for(let a=0;a<this.state.activeScope.track.length;a++){let s=this.state.activeScope.track[a];!s.kept&&!n.has(s.id)&&s.dispose()}let r=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(a=>{!a.kept&&a.scopeId===r.id&&this.track(a)})}gradients(e,t,n,r=!1){if(F(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let a=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));F(a instanceof je,()=>"The result y returned by f() must be a tensor.");let s=Xk(this.state.activeTape,t,a);if(!r&&s.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{let i={};i[a.id]=n==null?s9(a.shape):n,Kk(i,s,l=>this.tidy(l),i9);let o=t.map(l=>i[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:a,grads:o}})}customGrad(e){return F(Na(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{F(t.every(i=>i instanceof je),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,r={};t.forEach((i,o)=>{r[o]=i});let a=(i,o)=>(n=e(...t,o),F(n.value instanceof je,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),F(Na(n.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),n.value),s=(i,o)=>{let l=n.gradFunc(i,o),u=Array.isArray(l)?l:[l];F(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(...)."),F(u.every(h=>h instanceof je),()=>"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((h,d)=>{c[d]=()=>h}),c};return this.runKernelFunc({forwardFunc:a,backwardsFunc:s,inputs:r})}}readSync(e){return this.state.tensorInfo.get(e).backend.readSync(e)}read(e){return this.state.tensorInfo.get(e).backend.read(e)}async time(e){let t=Su(),n=await this.backend.time(e);return n.wallMs=Su()-t,n}track(e){return this.state.activeScope!=null&&(e.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(e)),e}get registeredVariables(){return this.state.registeredVariables}reset(){this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new l5;for(let e in this.registry)this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null}};Mu.nextTensorId=0;Mu.nextVariableId=0;function s9(e){let t=nf(Ot(e),"float32");return $.makeTensor(t,e,"float32")}function u5(){let e=e5();if(e._tfengine==null){let t=new Qg(e);e._tfengine=new Mu(t)}return Ok(e._tfengine.ENV),Qk(()=>e._tfengine),e._tfengine}var $=u5();function i9(e,t){let n={a:e,b:t};return $.runKernel(Ia,n)}var $u={};ze($u,{isBrowser:()=>c5,isMobile:()=>o9});function l9(){return typeof navigator!="undefined"&&navigator!=null}function o9(){if(l9()){let e=navigator.userAgent||navigator.vendor||window.opera;return/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(e)||/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(e.substr(0,4))}return!1}function c5(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var gr=J();gr.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. 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bM={kernelName:ms,backendName:"cpu",kernelFunc:_M};function vM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r;be([a,s],"conv3d");let u=R.computeConv3DInfo(a.shape,s.shape,i,l,o),{filterDepth:c,filterHeight:h,filterWidth:d,dilationDepth:p,dilationHeight:f,dilationWidth:m,padInfo:A}=u,y=A.front,g=A.left,w=A.top,b=new zt(u.outShape,a.dtype),_=n.data.get(a.dataId).values,x=n.data.get(s.dataId).values,I=b.values,S=v.computeStrides(a.shape),T=v.computeStrides(s.shape);for(let M=0;M<u.batchSize;++M){let D=M*S[0],z=M*b.strides[0];for(let B=0;B<u.outDepth;++B){let U=z+B*b.strides[1],j=B*u.strideDepth-y;for(let X=0;X<c;++X){let H=j+X*p;if(H<0||H>=u.inDepth)continue;let ee=X*T[0],Y=D+H*S[1];for(let ae=0;ae<u.outHeight;++ae){let te=U+ae*b.strides[2],ie=ae*u.strideHeight-w;for(let Q=0;Q<h;++Q){let he=ie+Q*f;if(he<0||he>=u.inHeight)continue;let le=ee+Q*T[1],fe=Y+he*S[2];for(let pe=0;pe<u.outWidth;++pe){let ke=te+pe*u.outChannels,Ie=pe*u.strideWidth-g;for(let 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zM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.data.get(a.dataId).values,u=n.data.get(s.dataId).values,c=Cm(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=qx(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var PM={kernelName:Mh,backendName:"cpu",kernelFunc:zM};function LM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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n.makeTensorInfo(a.shape,a.dtype,m)}var QM={kernelName:vs,backendName:"cpu",kernelFunc:JM};function eF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;_e([a],"batchToSpaceND");let o=s.reduce((y,g)=>y*g),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=yt({inputs:{x:a},backend:n,attrs:{shape:l}}),f=lr({inputs:{x:p},backend:n,attrs:{perm:c}}),m=yt({inputs:{x:f},backend:n,attrs:{shape:u}}),A=yi({inputs:{x:m},backend:n,attrs:{begin:h,size:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),A}var tF={kernelName:du,backendName:"cpu",kernelFunc:eF};function nF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.data.get(a.dataId).values,l=n.data.get(s.dataId).values,c=Cm(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var 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SF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r;_e(a,"cumsum");let l=R.getAxesPermutation([s],a.shape.length),c=a;l!=null&&(c=lr({inputs:{x:a},backend:n,attrs:{perm:l}}));let u=R.getInnerMostAxes(1,a.shape.length)[0];if(u!==c.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${c.shape.length-1} but got axis=${u}`);let h=ar(c.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(c.shape),h),p=n.data.get(c.dataId).values,f=c.shape[c.shape.length-1],m=o?(y,g)=>y+f-g-1:(y,g)=>y+g;for(let y=0;y<p.length;y+=f)for(let g=0;g<f;g++){let w=m(y,g);if(g===0)d[w]=i?0:p[w];else{let b=m(y,g-1);d[w]=i?p[b]+d[b]:p[w]+d[b]}}let A=n.makeTensorInfo(c.shape,h,d);if(l!=null){let y=R.getUndoAxesPermutation(l),g=lr({inputs:{x:A},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(A),n.disposeIntermediateTensorInfo(c),g}return A}var TF={kernelName:ys,backendName:"cpu",kernelFunc:SF};function CF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.data.get(a.dataId).values,c=n.data.get(s.dataId).values,u=Cm(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=Xx(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var EF={kernelName:$h,backendName:"cpu",kernelFunc:CF};function RF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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$F(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r;_e([a,s],"depthwiseConv2dNativeBackpropFilter");let h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),{strideHeight:d,strideWidth:p,filterHeight:f,filterWidth:m}=h,A=new zt(h.filterShape,"float32"),y=h.padInfo.left,g=h.padInfo.top,w=h.outChannels/h.inChannels,b=n.data.get(a.dataId).values,_=new zt(a.shape,a.dtype,b),x=n.data.get(s.dataId).values,N=new zt(s.shape,s.dtype,x);for(let T=0;T<f;++T){let C=Math.max(0,Math.ceil((g-T)/d)),F=Math.min(h.outHeight,(h.inHeight+g-T)/d);for(let z=0;z<m;++z){let B=Math.max(0,Math.ceil((y-z)/p)),V=Math.min(h.outWidth,(h.inWidth+y-z)/p);for(let U=0;U<h.outChannels;++U){let j=Math.trunc(U/w),X=U%w,G=0;for(let ee=0;ee<h.batchSize;++ee)for(let Y=C;Y<F;++Y){let ae=T+Y*d-g;for(let te=B;te<V;++te){let oe=z+te*p-y;G+=_.get(ee,ae,oe,j)*N.get(ee,Y,te,U)}}A.set(G,T,z,j,X)}}}return n.makeTensorInfo(A.shape,A.dtype,A.values)}var DF={kernelName:Dh,backendName:"cpu",kernelFunc:$F};function OF(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r;_e([a,s],"depthwiseConv2DNativeBackpropInput");let h=v.computeStrides(a.shape),d=v.computeStrides(s.shape),p=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),f=new zt(p.inShape,"float32"),m=f.values,[A,y,g]=f.strides,w=n.data.get(a.dataId).values,[b,_,x]=h,N=n.data.get(s.dataId).values,[T,C,F]=d,{batchSize:z,filterHeight:B,filterWidth:V,inChannels:U,inHeight:j,inWidth:X,outChannels:G,outHeight:ee,outWidth:Y,strideHeight:ae,strideWidth:te}=p,oe=B-1-p.padInfo.top,Q=V-1-p.padInfo.left,he=G/U;for(let le=0;le<z;++le)for(let fe=0;fe<U;++fe)for(let pe=0;pe<j;++pe){let ke=pe-oe,Ne=Math.max(0,Math.ceil(ke/ae)),Fe=Math.min(ee,(B+ke)/ae);for(let Oe=0;Oe<X;++Oe){let $e=Oe-Q,et=Math.max(0,Math.ceil($e/te)),tt=Math.min(Y,(V+$e)/te),ot=0;for(let Ye=Ne;Ye<Fe;++Ye){let dt=Ye*ae-ke;for(let Be=et;Be<tt;++Be){let yn=Be*te-$e,wt=b*le+_*Ye+x*Be,Un=T*(B-1-dt)+C*(V-1-yn)+F*fe;for(let Yt=0;Yt<he;++Yt){let gn=fe*he+Yt,jn=w[wt+gn],Rn=N[Un+Yt];ot+=jn*Rn}}}m[A*le+y*pe+g*Oe+fe]=ot}}return n.makeTensorInfo(f.shape,f.dtype,f.values)}var zF={kernelName:Oh,backendName:"cpu",kernelFunc:OF};function PF(e){let{inputs:t,backend:n}=e,{x:r}=t,a=v.sizeFromShape(r.shape),s=n.data.get(r.dataId).values,i=We([a,a],r.dtype),o=i.values;for(let c=0;c<s.length;c++)o[c*a+c]=s[c];let l=[...r.shape,...r.shape];return n.makeTensorInfo(l,i.dtype,i.values)}var 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e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function ua(e,t,n){let r=we(e,()=>t());if(r==null)throw new Error(n);return r}function ub(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,r=t+e.TEXTURE0;if(r<e.TEXTURE0||r>n){let a=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${a}.`)}}function gi(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function xi(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function ip(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[gi(e),...xi(e)]),t}function nb(e,t=!1){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((a,s)=>s>=e.length-2?v.nearestLargerEven(e[s]):e[s]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let r=v.sizeFromShape(e);if(e.length<=1&&r<=n)return[1,r];if(e.length===2&&e[0]<=n&&e[1]<=n)return e;if(e.length===3&&e[0]*e[1]<=n&&e[2]<=n)return[e[0]*e[1],e[2]];if(e.length===3&&e[0]<=n&&e[1]*e[2]<=n)return[e[0],e[1]*e[2]];if(e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n)return[e[0]*e[1]*e[2],e[3]];if(e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n)return[e[0],e[1]*e[2]*e[3]];if(t){let a=gi(e),s=2,i=2;return e.length&&([s,i]=xi(e)),r=a*(s/2)*(i/2),v.sizeToSquarishShape(r).map(o=>o*2)}return v.sizeToSquarishShape(r)}function lp(e){return e%2==0}function oc(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e.slice(-1)[0],r=t.slice(-1)[0];if(n===r||lp(n)&&lp(r)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&lp(e[0])&&lp(t[0])}var up,cp;function rb(e){if(up==null){let t=Vr(e);up=t.getParameter(t.MAX_TEXTURE_SIZE)}return up}function lz(){up=null}function uz(){cp=null}function ab(e){if(cp==null){let t=Vr(e);cp=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,cp)}function sb(e){if(e===0)return 0;let t,n=Vr(e);return Zn(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:Zn(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function Zn(e,t){return e.getExtension(t)!=null}function Hm(e){try{if(Vr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function ib(e){if(e===0)return!1;let t=Vr(e);if(e===1){if(!Zn(t,"OES_texture_float"))return!1}else if(!Zn(t,"EXT_color_buffer_float"))return!1;return Xm(t)}function ob(e){if(e===0)return!1;let t=Vr(e);if(e===1){if(!Zn(t,"OES_texture_float")||!Zn(t,"WEBGL_color_buffer_float"))return!1}else{if(Zn(t,"EXT_color_buffer_float"))return Xm(t);let n="EXT_color_buffer_half_float";if(Zn(t,n)){let r=t.getExtension(n);return xz(t,r)}return!1}return Xm(t)}function Xm(e){let t=qm(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,r,a,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(s),i}function xz(e,t){let n=qm(e,t),r=e.createTexture();e.bindTexture(e.TEXTURE_2D,r);let a=1,s=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,a,s,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,r,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(r),e.deleteFramebuffer(i),o}function lb(e){return e!==2?!1:Vr(e).fenceSync!=null}function kl(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Me=J();Me.registerFlag("HAS_WEBGL",()=>Me.getNumber("WEBGL_VERSION")>0);Me.registerFlag("WEBGL_VERSION",()=>Hm(2)?2:Hm(1)?1:0);Me.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Me.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Me.get("WEBGL_VERSION")===2);Me.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Me.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Me.registerFlag("WEBGL_PACK",()=>Me.getBool("HAS_WEBGL"));Me.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_CLIP",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>!1);Me.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_REDUCE",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_LAZILY_UNPACK",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_CONV_IM2COL",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>rb(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>ab(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Me.getNumber("WEBGL_VERSION");return e===0?0:sb(e)});Me.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Me.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Du.isMobile());Me.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>ib(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Me.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Me.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Me.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>ob(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_FENCE_API_ENABLED",()=>lb(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Me.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Me.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});Me.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Du.isMobile()&&Me.getBool("IS_CHROME")?1:-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});function fn(){let e,t,n,r,a,s,i,o,l,c;return J().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",r="in",a="texture",s="outputColor",i="out vec4 outputColor;",o=`
       bool isnan_custom(float val) {
         return (val > 0.0 || val < 0.0) ? false : val != 0.0;
       }
@@ -40,7 +40,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       }
 
       #define isnan(value) isnan_custom(value)
-    `,l="",u=`
+    `,l="",c=`
       #define round(value) newRound(value)
       int newRound(float value) {
         return int(floor(value + 0.5));
@@ -66,7 +66,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       bvec4 isinf(vec4 val) {
         return equal(abs(val), vec4(INFINITY));
       }
-    `,u=`
+    `,c=`
       int round(float value) {
         return int(floor(value + 0.5));
       }
@@ -74,11 +74,11 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       ivec4 round(vec4 value) {
         return ivec4(floor(value + vec4(0.5)));
       }
-    `),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:u}}function _i(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function Km(e){let t=v.computeStrides(e).map(n=>n.toString());return`
+    `),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:c}}function bi(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function Km(e){let t=v.computeStrides(e).map(n=>n.toString());return`
   int getFlatIndex(ivec3 coords) {
     return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
   }
-`}var u_=`
+`}var cb=`
   const float FLOAT_MAX = 1.70141184e38;
   const float FLOAT_MIN = 1.17549435e-38;
 
@@ -117,9 +117,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
     return c / 255.0;
   }
-`,Tz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=oc.DENSE;let t=uc(e),n=fn();this.outputShape=e,this.userCode=`
+`,wz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=lc.DENSE;let t=cc(e),n=fn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${_i(["r","c","d"],e)}
+        ${bi(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -138,9 +138,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},Cz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=oc.DENSE;let t=uc(e),n=fn();this.outputShape=e,this.userCode=`
+    `}},bz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=lc.DENSE;let t=cc(e),n=fn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${_i(["r","c","d"],e)}
+        ${bi(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -159,22 +159,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},Ez=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Yn.DOWNLOAD;let t=fn();this.outputShape=e,this.userCode=`
-      ${u_}
+    `}},_z=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Yn.DOWNLOAD;let t=fn();this.outputShape=e,this.userCode=`
+      ${cb}
 
       void main() {
         float x = getAAtOutCoords();
         ${t.output} = encode_float(x);
       }
-    `}},Rz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Yn.DOWNLOAD;let t=fn();this.outputShape=e,this.userCode=`
-      ${u_}
+    `}},vz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Yn.DOWNLOAD;let t=fn();this.outputShape=e,this.userCode=`
+      ${cb}
 
       void main() {
         ivec3 coords = getOutputCoords();
         float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
         ${t.output} = encode_float(x);
       }
-    `}},Fz=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=fn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
+    `}},kz=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=fn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
       ${Km(e)}
 
       void main() {
@@ -204,10 +204,10 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = vec4(${i}, 0., 0., 0.);
       }
-    `}},Mz=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=fn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let u=0;u<=1;u++){let c=l*2+u;i+=`
+    `}},Iz=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=fn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let c=0;c<=1;c++){let u=l*2+c;i+=`
           localCoords = coords;
-          if(localCoords[2] + ${u} < ${e[2]}) {
-            localCoords[2] += ${u};
+          if(localCoords[2] + ${c} < ${e[2]}) {
+            localCoords[2] += ${c};
             if(localCoords[1] + ${l} < ${e[1]}) {
               localCoords[1] += ${l};
 
@@ -222,13 +222,13 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
               values = ${r.texture2D}(A, uv);
 
               if(offset == 0) {
-                result[${c}] = values[0];
+                result[${u}] = values[0];
               } else if(offset == 1) {
-                result[${c}] = values[1];
+                result[${u}] = values[1];
               } else if(offset == 2) {
-                result[${c}] = values[2];
+                result[${u}] = values[2];
               } else {
-                result[${c}] = values[3];
+                result[${u}] = values[3];
               }
             }
           }
@@ -248,7 +248,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = ${o};
       }
-    `}},c_={};ze(c_,{bindVertexProgramAttributeStreams:()=>x_,createBufferFromOutputTexture:()=>b_,createFloat16MatrixTexture:()=>m_,createFloat16PackedMatrixTexture:()=>g_,createFloat32MatrixTexture:()=>f_,createIndexBuffer:()=>p_,createPackedMatrixTexture:()=>y_,createUnsignedBytesMatrixTexture:()=>A_,createVertexBuffer:()=>d_,createVertexShader:()=>h_,downloadByteEncodedFloatMatrixFromOutputTexture:()=>k_,downloadFloat32MatrixFromBuffer:()=>v_,downloadMatrixFromPackedOutputTexture:()=>I_,downloadPackedMatrixFromBuffer:()=>N_,getInternalFormatForFloat16MatrixTexture:()=>Ym,getInternalFormatForFloat16PackedMatrixTexture:()=>eA,getInternalFormatForFloat32MatrixTexture:()=>Zm,getInternalFormatForPackedMatrixTexture:()=>Qm,getInternalFormatForUnsignedBytesMatrixTexture:()=>Jm,uploadDenseMatrixToTexture:()=>w_,uploadPixelDataToTexture:()=>__});function h_(e){let t=fn(),n=`${t.version}
+    `}},hb={};ze(hb,{bindVertexProgramAttributeStreams:()=>wb,createBufferFromOutputTexture:()=>vb,createFloat16MatrixTexture:()=>Ab,createFloat16PackedMatrixTexture:()=>xb,createFloat32MatrixTexture:()=>mb,createIndexBuffer:()=>fb,createPackedMatrixTexture:()=>gb,createUnsignedBytesMatrixTexture:()=>yb,createVertexBuffer:()=>pb,createVertexShader:()=>db,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Ib,downloadFloat32MatrixFromBuffer:()=>kb,downloadMatrixFromPackedOutputTexture:()=>Sb,downloadPackedMatrixFromBuffer:()=>Nb,getInternalFormatForFloat16MatrixTexture:()=>Ym,getInternalFormatForFloat16PackedMatrixTexture:()=>eA,getInternalFormatForFloat32MatrixTexture:()=>Zm,getInternalFormatForPackedMatrixTexture:()=>Qm,getInternalFormatForUnsignedBytesMatrixTexture:()=>Jm,uploadDenseMatrixToTexture:()=>bb,uploadPixelDataToTexture:()=>_b});function db(e){let t=fn(),n=`${t.version}
     precision highp float;
     ${t.attribute} vec3 clipSpacePos;
     ${t.attribute} vec2 uv;
@@ -257,22 +257,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
     void main() {
       gl_Position = vec4(clipSpacePos, 1);
       resultUV = uv;
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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;we(e,()=>e.finish()),we(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),we(e,()=>e.deleteFramebuffer(this.framebuffer)),we(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),we(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),we(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),mb(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),Ab(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),yb(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),_b(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,r){this.throwIfDisposed(),bb(this.gl,e,t,n,r,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),xb(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),gb(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(jm(this.gl,this.framebuffer),this.outputTexture=null),we(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Ib(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,r,a,s){return Nb(this.gl,e,t,n,r,a,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return kb(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let r=vb(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(J().getBool("WEBGL_FENCE_API_ENABLED")){let r=e,a=r.fenceSync(r.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let s=r.clientWaitSync(a,0,0);return s===r.ALREADY_SIGNALED||s===r.CONDITION_SATISFIED},t=a}else J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Sb(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=Uw(t,e),r=db(t),a=jw(t);return we(t,()=>t.attachShader(a,r)),we(t,()=>t.attachShader(a,n)),Hw(t,a),this.debug&&ap(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=wb(t,this.program,this.vertexBuffer)),a}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&we(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&ap(this.gl,this.program),we(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?Jw(this.gl,e,t):Qw(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),we(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(),eb(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[r,a]=Il(t,n);this.setOutputMatrixTextureDriver(e,r,a)}setOutputMatrixWriteRegion(e,t,n,r){this.setOutputMatrixWriteRegionDriver(n,e,r,t)}setOutputPackedMatrixWriteRegion(e,t,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&ap(this.gl,this.program),ic(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),we(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),we(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=sc(this.gl,J().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(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.createQuery();return n.beginQuery(r.TIME_ELAPSED_EXT,a),a}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),a&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),r=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=Nz(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),sp(this.gl,e,this.framebuffer),this.debug&&ic(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(sp(this.gl,this.outputTexture,this.framebuffer),this.debug&&ic(this.gl)):jm(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;sp(r,e,this.framebuffer),this.debug&&ic(r),this.outputTexture=e,we(r,()=>r.viewport(0,0,t,n)),we(r,()=>r.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,r){this.throwIfDisposed(),we(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 Nz(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:Tb}=R;function Dz(e,t,n,r){let a=[];e.forEach(p=>{let f=v.sizeFromShape(p.shapeInfo.logicalShape);p.shapeInfo.isUniform?a.push(`uniform float ${p.name}${f>1?`[${f}]`:""};`):(a.push(`uniform sampler2D ${p.name};`),a.push(`uniform int offset${p.name};`))});let s=a.join(`
+`),i=e.map(p=>Sz(p,t,r)).join(`
+`),o=t.texShape,l=fn(),c=Ez(l),u,h,d=Fz(l);return t.isPacked?(u=Tz(t.logicalShape,o),h=Mz(l)):(u=Cz(t.logicalShape,o),h=Rz(l)),r&&(d+=$z),[d,c,h,s,u,i,n].join(`
+`)}function Nl(e){let t=e.shapeInfo.logicalShape;switch(t.length){case 0:return Oz(e);case 1:return zz(e);case 2:return Pz(e);case 3:return Lz(e);case 4:return Wz(e);case 5:return Bz(e);case 6:return Vz(e);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function Cb(e){switch(e.shapeInfo.logicalShape.length){case 0:return Uz(e);case 1:return jz(e);case 2:return Hz(e);case 3:return Gz(e);default:return qz(e)}}function Sz(e,t,n=!1){let r="";n?r+=Cb(e):r+=Nl(e);let a=e.shapeInfo.logicalShape,s=t.logicalShape;return a.length<=s.length&&(n?r+=Xz(e,t):r+=Kz(e,t)),r}function Tz(e,t){switch(e.length){case 0:return Eb();case 1:return Zz(e,t);case 2:return Qz(e,t);case 3:return Yz(e,t);default:return Jz(e,t)}}function Cz(e,t){switch(e.length){case 0:return Eb();case 1:return eP(e,t);case 2:return sP(e,t);case 3:return tP(e,t);case 4:return nP(e,t);case 5:return rP(e,t);case 6:return aP(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function Ez(e){return`
     float sampleTexture(sampler2D textureSampler, vec2 uv) {
       return ${e.texture2D}(textureSampler, uv).r;
     }
-  `}function Lz(e){return`
+  `}function Rz(e){return`
     void setOutput(float val) {
       ${e.output} = vec4(val, 0, 0, 0);
     }
-  `}function Wz(e){return`
+  `}function Mz(e){return`
     void setOutput(vec4 val) {
       ${e.output} = val;
     }
-  `}function Bz(e){return`${e.version}
+  `}function Fz(e){return`${e.version}
     precision highp float;
     precision highp int;
     precision highp sampler2D;
@@ -327,10 +327,10 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       return fract((p3.x + p3.y) * p3.z);
     }
 
-    ${fP}
-    ${mP}
-    ${AP}
-  `}var fP=`
+    ${iP}
+    ${oP}
+    ${lP}
+  `}var iP=`
 vec2 uvFromFlat(int texNumR, int texNumC, int index) {
   int texR = index / texNumC;
   int texC = index - texR * texNumC;
@@ -342,7 +342,7 @@ vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,mP=`
+`,oP=`
 vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texNumC, int row, int col) {
   int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
@@ -350,7 +350,7 @@ vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,AP=`
+`,lP=`
 vec2 packedUVfrom3D(int texNumR, int texNumC,
     int texelsInBatch, int texelsInLogicalRow, int b,
     int row, int col) {
@@ -359,7 +359,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   int texC = index - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,Vz=`
+`,$z=`
   float getChannel(vec4 frag, vec2 innerDims) {
     vec2 modCoord = mod(innerDims, 2.);
     return modCoord.x == 0. ?
@@ -370,11 +370,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     float modCoord = mod(float(dim), 2.);
     return modCoord == 0. ? frag.r : frag.g;
   }
-`;function C_(){return`
+`;function Eb(){return`
     int getOutputCoords() {
       return 0;
     }
-  `}function aP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
+  `}function Zz(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 * ${n[1]}.0);
       }
@@ -388,7 +388,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${n[0]}, ${n[1]}));
       return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
     }
-  `}function lP(e,t){return t[0]===1?`
+  `}function eP(e,t){return t[0]===1?`
       int getOutputCoords() {
         return int(resultUV.x * ${t[1]}.0);
       }
@@ -402,7 +402,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${t[0]}, ${t[1]}));
       return resTexRC.x * ${t[1]} + resTexRC.y;
     }
-  `}function sP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
+  `}function Yz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${n[0]}, ${n[1]}));
@@ -416,7 +416,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec3(b, r, c);
     }
-  `}function uP(e,t){let n=_i(["r","c","d"],e);return`
+  `}function tP(e,t){let n=bi(["r","c","d"],e);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${t[0]}, ${t[1]}));
@@ -424,7 +424,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec3(r, c, d);
     }
-  `}function iP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
+  `}function Jz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
       int b${l} = index / ${s};
       index -= b${l} * ${s};
     `+i,o=`b${l}, `+o;return`
@@ -443,7 +443,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec${e.length}(${o});
     }
-  `}function cP(e,t){let n=_i(["r","c","d","d2"],e);return`
+  `}function nP(e,t){let n=bi(["r","c","d","d2"],e);return`
     ivec4 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -451,7 +451,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec4(r, c, d, d2);
     }
-  `}function hP(e,t){let n=_i(["r","c","d","d2","d3"],e);return`
+  `}function rP(e,t){let n=bi(["r","c","d","d2","d3"],e);return`
     ivec5 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                              ${t[1]}));
@@ -463,7 +463,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec5 outShape = ivec5(r, c, d, d2, d3);
       return outShape;
     }
-  `}function dP(e,t){let n=_i(["r","c","d","d2","d3","d4"],e);return`
+  `}function aP(e,t){let n=bi(["r","c","d","d2","d3","d4"],e);return`
     ivec6 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -474,7 +474,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec6 result = ivec6(r, c, d, d2, d3, d4);
       return result;
     }
-  `}function oP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
+  `}function Qz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
       ivec2 getOutputCoords() {
         return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
       }
@@ -489,7 +489,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec2(r, c);
     }
-  `}function pP(e,t){return v.arraysEqual(e,t)?`
+  `}function sP(e,t){return v.arraysEqual(e,t)?`
       ivec2 getOutputCoords() {
         return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
       }
@@ -516,26 +516,26 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       int c = index - r * ${e[1]};
       return ivec2(r, c);
     }
-  `}function bi(e){return`offset${e}`}function Yz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=fn();return`
+  `}function _i(e){return`offset${e}`}function Uz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=fn();return`
     vec4 ${n}() {
       return ${r.texture2D}(${t}, halfCR);
     }
-  `}function jz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
+  `}function Oz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
       float ${n}() {
         return sampleTexture(${t}, halfCR);
       }
-    `;let[s,i]=e.shapeInfo.texShape,o=bi(t);return`
+    `;let[s,i]=e.shapeInfo.texShape,o=_i(t);return`
     float ${n}() {
       vec2 uv = uvFromFlat(${s}, ${i}, ${o});
       return sampleTexture(${t}, uv);
     }
-  `}function Jz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=fn();return`
+  `}function jz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=fn();return`
     vec4 ${n}(int index) {
       vec2 uv = packedUVfrom1D(
         ${a[0]}, ${a[1]}, index);
       return ${s.texture2D}(${t}, uv);
     }
-  `}function Hz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
+  `}function zz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
       float ${n}(int index) {
         ${Sl(e)}
       }
@@ -543,7 +543,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       float ${n}(int index) {
         return sampleTexture(${t}, halfCR);
       }
-    `;let i=bi(t);return s===1?`
+    `;let i=_i(t);return s===1?`
       float ${n}(int index) {
         vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / ${a}.0);
         return sampleTexture(${t}, uv);
@@ -558,24 +558,24 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${a}, ${s}, index + ${i});
       return sampleTexture(${t}, uv);
     }
-  `}function Qz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=fn();if(a!=null&&v.arraysEqual(t,a))return`
+  `}function Hz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=fn();if(a!=null&&v.arraysEqual(t,a))return`
       vec4 ${r}(int row, int col) {
         vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${s}.0);
 
         return ${o.texture2D}(${n}, uv);
       }
-    `;let l=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],u=Math.ceil(t[1]/2);return`
+    `;let l=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],c=Math.ceil(t[1]/2);return`
     vec4 ${r}(int row, int col) {
-      vec2 uv = packedUVfrom2D(${u}, ${l[0]}, ${l[1]}, row, col);
+      vec2 uv = packedUVfrom2D(${c}, ${l[0]}, ${l[1]}, row, col);
       return ${o.texture2D}(${n}, uv);
     }
-  `}function Gz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
+  `}function Pz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
     float ${r}(int row, int col) {
       vec2 uv = (vec2(col, row) + halfCR) / vec2(${d}.0, ${h}.0);
       return sampleTexture(${n}, uv);
     }
   `}let{newShape:s,keptDims:i}=v.squeezeShape(t),o=s;if(o.length<t.length){let h=Tl(e,o),d=["row","col"];return`
-      ${Il(h)}
+      ${Nl(h)}
       float ${r}(int row, int col) {
         return ${r}(${Cl(d,i)});
       }
@@ -584,38 +584,38 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         int index = round(dot(vec2(row, col), vec2(${t[1]}, 1)));
         ${Sl(e)}
       }
-    `;let l=a[0],u=a[1],c=bi(n);return u===1?`
+    `;let l=a[0],c=a[1],u=_i(n);return c===1?`
     float ${r}(int row, int col) {
-      float index = dot(vec3(row, col, ${c}), vec3(${t[1]}, 1, 1));
+      float index = dot(vec3(row, col, ${u}), vec3(${t[1]}, 1, 1));
       vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
       return sampleTexture(${n}, uv);
     }
   `:l===1?`
     float ${r}(int row, int col) {
-      float index = dot(vec3(row, col, ${c}), vec3(${t[1]}, 1, 1));
-      vec2 uv = vec2((index + 0.5) / ${u}.0, 0.5);
+      float index = dot(vec3(row, col, ${u}), vec3(${t[1]}, 1, 1));
+      vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
       return sampleTexture(${n}, uv);
     }
   `:`
   float ${r}(int row, int col) {
     // Explicitly use integer operations as dot() only works on floats.
-    int index = row * ${t[1]} + col + ${c};
-    vec2 uv = uvFromFlat(${l}, ${u}, index);
+    int index = row * ${t[1]} + col + ${u};
+    vec2 uv = uvFromFlat(${l}, ${c}, index);
     return sampleTexture(${n}, uv);
   }
-`}function eP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=Tl(e,h),f=["b","row","col"];return`
-        ${T_(p)}
+`}function Gz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=Tl(e,h),f=["b","row","col"];return`
+        ${Cb(p)}
         vec4 ${r}(int b, int row, int col) {
           return ${r}(${Cl(f,d)});
         }
-      `}let i=s[0],o=s[1],l=Math.ceil(t[2]/2),u=l*Math.ceil(t[1]/2),c=fn();return`
+      `}let i=s[0],o=s[1],l=Math.ceil(t[2]/2),c=l*Math.ceil(t[1]/2),u=fn();return`
     vec4 ${r}(int b, int row, int col) {
       vec2 uv = packedUVfrom3D(
-        ${i}, ${o}, ${u}, ${l}, b, row, col);
-      return ${c.texture2D}(${n}, uv);
+        ${i}, ${o}, ${c}, ${l}, b, row, col);
+      return ${u.texture2D}(${n}, uv);
     }
-  `}function qz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=Tl(e,l),m=["row","col","depth"];return`
-        ${Il(f)}
+  `}function Lz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=Tl(e,l),m=["row","col","depth"];return`
+        ${Nl(f)}
         float ${r}(int row, int col, int depth) {
           return ${r}(${Cl(m,o)});
         }
@@ -625,29 +625,29 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                           vec3(${a}, ${s}, 1)));
         ${Sl(e)}
       }
-    `;let u=e.shapeInfo.texShape,c=u[0],h=u[1],d=e.shapeInfo.flatOffset;if(h===a&&d==null)return`
+    `;let c=e.shapeInfo.texShape,u=c[0],h=c[1],d=e.shapeInfo.flatOffset;if(h===a&&d==null)return`
         float ${r}(int row, int col, int depth) {
           float texR = float(row);
           float texC = dot(vec2(col, depth), vec2(${s}, 1));
           vec2 uv = (vec2(texC, texR) + halfCR) /
-                     vec2(${h}.0, ${c}.0);
+                     vec2(${h}.0, ${u}.0);
           return sampleTexture(${n}, uv);
         }
       `;if(h===s&&d==null)return`
     float ${r}(int row, int col, int depth) {
       float texR = dot(vec2(row, col), vec2(${t[1]}, 1));
       float texC = float(depth);
-      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${h}.0, ${c}.0);
+      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${h}.0, ${u}.0);
       return sampleTexture(${n}, uv);
     }
-  `;let p=bi(n);return`
+  `;let p=_i(n);return`
       float ${r}(int row, int col, int depth) {
         // Explicitly use integer operations as dot() only works on floats.
         int index = row * ${a} + col * ${s} + depth + ${p};
-        vec2 uv = uvFromFlat(${c}, ${h}, index);
+        vec2 uv = uvFromFlat(${u}, ${h}, index);
         return sampleTexture(${n}, uv);
       }
-  `}function tP(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],u=Math.ceil(t[n-1]/2),c=u*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,c*=t[n-f-1],d=`b${f} * ${c} + `+d;let p=fn();return`
+  `}function qz(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],c=Math.ceil(t[n-1]/2),u=c*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${u} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,u*=t[n-f-1],d=`b${f} * ${u} + `+d;let p=fn();return`
     vec4 ${a}(${h}) {
       int index = ${d};
       int texR = index / ${l};
@@ -655,8 +655,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${o});
       return ${p.texture2D}(${r}, uv);
     }
-  `}function Xz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=Tl(e,o),m=["row","col","depth","depth2"];return`
-      ${Il(f)}
+  `}function Wz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=Tl(e,o),m=["row","col","depth","depth2"];return`
+      ${Nl(f)}
       float ${r}(int row, int col, int depth, int depth2) {
         return ${r}(${Cl(m,l)});
       }
@@ -666,7 +666,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                           vec4(${i}, ${s}, ${a}, 1)));
         ${Sl(e)}
       }
-    `;let u=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,h=c[0],d=c[1];if(d===i&&u==null)return`
+    `;let c=e.shapeInfo.flatOffset,u=e.shapeInfo.texShape,h=u[0],d=u[1];if(d===i&&c==null)return`
       float ${r}(int row, int col, int depth, int depth2) {
         float texR = float(row);
         float texC =
@@ -676,7 +676,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                    vec2(${d}.0, ${h}.0);
         return sampleTexture(${n}, uv);
       }
-    `;if(d===a&&u==null)return`
+    `;if(d===a&&c==null)return`
       float ${r}(int row, int col, int depth, int depth2) {
         float texR = dot(vec3(row, col, depth),
                          vec3(${t[1]*t[2]}, ${t[2]}, 1));
@@ -685,7 +685,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${d}.0, ${h}.0);
         return sampleTexture(${n}, uv);
       }
-    `;let p=bi(n);return`
+    `;let p=_i(n);return`
     float ${r}(int row, int col, int depth, int depth2) {
       // Explicitly use integer operations as dot() only works on floats.
       int index = row * ${i} + col * ${s} +
@@ -693,10 +693,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${h}, ${d}, index + ${p});
       return sampleTexture(${n}, uv);
     }
-  `}function Kz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let m=Tl(e,l),A=["row","col","depth","depth2","depth3"];return`
-      ${Il(m)}
+  `}function Bz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:c}=v.squeezeShape(t);if(l.length<t.length){let m=Tl(e,l),A=["row","col","depth","depth2","depth3"];return`
+      ${Nl(m)}
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
-        return ${r}(${Cl(A,u)});
+        return ${r}(${Cl(A,c)});
       }
     `}if(e.shapeInfo.isUniform)return`
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
@@ -706,7 +706,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           depth3;
         ${Sl(e)}
       }
-    `;let c=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,d=h[0],p=h[1];if(p===o&&c==null)return`
+    `;let u=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,d=h[0],p=h[1];if(p===o&&u==null)return`
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
         int texR = row;
         float texC = dot(vec4(col, depth, depth2, depth3),
@@ -715,7 +715,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                    vec2(${p}.0, ${d}.0);
         return sampleTexture(${n}, uv);
       }
-    `;if(p===a&&c==null)return`
+    `;if(p===a&&u==null)return`
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
         float texR = dot(
           vec4(row, col, depth, depth2),
@@ -726,7 +726,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${p}.0, ${d}.0);
         return sampleTexture(${n}, uv);
       }
-    `;let f=bi(n);return`
+    `;let f=_i(n);return`
     float ${r}(int row, int col, int depth, int depth2, int depth3) {
       // Explicitly use integer operations as dot() only works on floats.
       int index = row * ${o} + col * ${i} + depth * ${s} +
@@ -734,29 +734,29 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${d}, ${p}, index);
       return sampleTexture(${n}, uv);
     }
-  `}function Zz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=Tl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
-      ${Il(A)}
+  `}function Vz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=Tl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
+      ${Nl(A)}
       float ${r}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
         return ${r}(${Cl(y,s)});
       }
-    `}let i=t[5],o=t[4]*i,l=t[3]*o,u=t[2]*l,c=t[1]*u;if(e.shapeInfo.isUniform)return`
+    `}let i=t[5],o=t[4]*i,l=t[3]*o,c=t[2]*l,u=t[1]*c;if(e.shapeInfo.isUniform)return`
       float ${r}(int row, int col, int depth,
                   int depth2, int depth3, int depth4) {
         int index = round(dot(
           vec4(row, col, depth, depth2),
-          vec4(${c}, ${u}, ${l}, ${o})) +
+          vec4(${u}, ${c}, ${l}, ${o})) +
           dot(
             vec2(depth3, depth4),
             vec2(${i}, 1)));
         ${Sl(e)}
       }
-    `;let h=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,p=d[0],f=d[1];if(f===c&&h==null)return`
+    `;let h=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,p=d[0],f=d[1];if(f===u&&h==null)return`
       float ${r}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
         int texR = row;
         float texC = dot(vec4(col, depth, depth2, depth3),
-          vec4(${u}, ${l}, ${o}, ${i})) +
+          vec4(${c}, ${l}, ${o}, ${i})) +
                float(depth4);
         vec2 uv = (vec2(texC, texR) + halfCR) /
                    vec2(${f}.0, ${p}.0);
@@ -775,11 +775,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${f}.0, ${p}.0);
         return sampleTexture(${n}, uv);
       }
-    `;let m=bi(n);return`
+    `;let m=_i(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} +
+      int index = row * ${u} + col * ${c} + depth * ${l} +
           depth2 * ${o} + depth3 * ${i} + depth4 + ${m};
       vec2 uv = uvFromFlat(${p}, ${f}, index);
       return sampleTexture(${n}, uv);
@@ -790,8 +790,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         return ${t}[i];
       }
     }
-  `}function nP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=S_(e.shapeInfo.logicalShape,t.logicalShape),l=ct(i),u=i-s,c,h=["x","y","z","w","u","v"];s===0?c="":i<2&&o.length>=1?c="coords = 0;":c=o.map(A=>`coords.${h[A+u]} = 0;`).join(`
-`);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((A,y)=>`coords.${h[y+u]}`).join(", ");let p="return outputValue;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)p=`
+  `}function Xz(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Tb(e.shapeInfo.logicalShape,t.logicalShape),l=ut(i),c=i-s,u,h=["x","y","z","w","u","v"];s===0?u="":i<2&&o.length>=1?u="coords = 0;":u=o.map(A=>`coords.${h[A+c]} = 0;`).join(`
+`);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((A,y)=>`coords.${h[y+c]}`).join(", ");let p="return outputValue;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)p=`
       return vec4(outputValue.xy, outputValue.xy);
     `;else if(f&&!m)i===1?p=`
         return vec4(outputValue.x, outputValue.x, 0., 0.);
@@ -800,26 +800,26 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       `;else if(o.length){let A=s-2,y=s-1;o.indexOf(A)>-1&&o.indexOf(y)>-1?p="return vec4(outputValue.x);":o.indexOf(A)>-1?p="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(y)>-1&&(p="return vec4(outputValue.xx, outputValue.zz);")}return`
     vec4 ${a}() {
       ${l} coords = getOutputCoords();
-      ${c}
+      ${u}
       vec4 outputValue = get${r}(${d});
       ${p}
     }
-  `}function rP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
+  `}function Kz(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
       float ${a}() {
         return sampleTexture(${n}, resultUV);
       }
-    `;let u=ct(l),c=S_(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&c.length>=1?d="coords = 0;":d=c.map(m=>`coords.${p[m+h]} = 0;`).join(`
+    `;let c=ut(l),u=Tb(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&u.length>=1?d="coords = 0;":d=u.map(m=>`coords.${p[m+h]} = 0;`).join(`
 `);let f="";return l<2&&o>0?f="coords":f=e.shapeInfo.logicalShape.map((m,A)=>`coords.${p[A+h]}`).join(", "),`
     float ${a}() {
-      ${u} coords = getOutputCoords();
+      ${c} coords = getOutputCoords();
       ${d}
       return get${r}(${f});
     }
-  `}function ct(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Tl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function Cl(e,t){return t.map(n=>e[n]).join(", ")}function yP(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=Uz(s,o,a,t.packedInputs),u=e.createProgram(l),c=null,h=e.getUniformLocation(u,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(c=e.getUniformLocation(u,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(u,f,m),d[`offset${f}`]=e.getUniformLocation(u,`offset${f}`,m)}return{program:t,source:l,webGLProgram:u,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:c,nanLoc:h}}function E_(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function gP(e,t,n,r,a){E_(t.inShapeInfos,n),E_([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let u=t.program.variableNames[l],c=t.uniformLocations[u],h=t.uniformLocations[`offset${u}`];if(c!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(c,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(c,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,c,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function xP(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:wP,bincountImpl:R_,bincountReduceImpl:_P,ceilImpl:bP,concatImpl:vP,expImpl:kP,expm1Impl:NP,floorImpl:IP,gatherV2Impl:SP,greaterImpl:TP,lessImpl:CP,linSpaceImpl:EP,logImpl:RP,maxImpl:FP,maximumImpl:MP,minimumImpl:$P,multiplyImpl:DP,negImpl:OP,prodImpl:zP,rangeImpl:PP,rsqrtImpl:LP,simpleAbsImpl:F_,sliceImpl:WP,stridedSliceImpl:BP,subImpl:VP,tileImpl:UP,topKImpl:jP,transposeImpl:tA,uniqueImpl:HP}=Tm;function M_(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function mn(e,t){return t===1?[e]:M_(e,t)}function GP(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var ZP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
+  `}function ut(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Tl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function Cl(e,t){return t.map(n=>e[n]).join(", ")}function uP(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=Dz(s,o,a,t.packedInputs),c=e.createProgram(l),u=null,h=e.getUniformLocation(c,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(c,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(c,f,m),d[`offset${f}`]=e.getUniformLocation(c,`offset${f}`,m)}return{program:t,source:l,webGLProgram:c,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:u,nanLoc:h}}function Rb(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function cP(e,t,n,r,a){Rb(t.inShapeInfos,n),Rb([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let c=t.program.variableNames[l],u=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`];if(u!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(u,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(u,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,u,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function hP(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:dP,bincountImpl:Mb,bincountReduceImpl:pP,ceilImpl:fP,concatImpl:mP,expImpl:AP,expm1Impl:yP,floorImpl:gP,gatherV2Impl:xP,greaterImpl:wP,lessImpl:bP,linSpaceImpl:_P,logImpl:vP,maxImpl:kP,maximumImpl:IP,minimumImpl:NP,multiplyImpl:SP,negImpl:TP,prodImpl:CP,rangeImpl:EP,rsqrtImpl:RP,simpleAbsImpl:Fb,sliceImpl:MP,stridedSliceImpl:FP,subImpl:$P,tileImpl:DP,topKImpl:OP,transposeImpl:tA,uniqueImpl:zP}=Tm;function $b(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function mn(e,t){return t===1?[e]:$b(e,t)}function PP(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var VP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
         void main() {
           setOutput(vec4(getA(), 0., 0., 0.));
         }
-      `;else{let n=mn("rc",t),r=ct(t),a=qP(t,e,n),s=XP(t,e[e.length-1],e[e.length-2],n),i=KP(e,n);this.userCode=`
+      `;else{let n=mn("rc",t),r=ut(t),a=LP(t,e,n),s=WP(t,e[e.length-1],e[e.length-2],n),i=BP(e,n);this.userCode=`
         void main() {
           ${r} rc = getOutputCoords();
 
@@ -831,7 +831,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             setOutput(vec4(${i}));
           }
         }
-      `}}};function YP(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function qP(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function XP(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
+      `}}};function UP(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function LP(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function WP(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
     int r = ${a[0]};
     int c = ${a[1]};
     int rp1 = r + 1;
@@ -839,12 +839,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
     bool cEdge = cp1 >= ${t};
     bool rEdge = rp1 >= ${n};
-  `}function KP(e,t){let n=e.length,r=YP(n,t);return n===1?`getA(rc),
+  `}function BP(e,t){let n=e.length,r=UP(n,t);return n===1?`getA(rc),
             rc + 1 >= ${e[0]} ? 0. : getA(rc + 1),
             0, 0`:`getA(${r[0]}),
           cEdge ? 0. : getA(${r[1]}),
           rEdge ? 0. : getA(${r[2]}),
-          rEdge || cEdge ? 0. : getA(${r[3]})`}var $_=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
+          rEdge || cEdge ? 0. : getA(${r[3]})`}var Db=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
         ${a}
         ${r>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
           int flatIndex = getFlatIndex(thisRC);
@@ -856,7 +856,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
         ${r>0?"}":""}
       `}this.userCode=`
-      ${JP(t)}
+      ${jP(t)}
       ${Km(e)}
 
       void main() {
@@ -872,12 +872,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function JP(e){return`
+    `}};function jP(e){return`
     ivec3 inputCoordsFromReshapedOutCoords(int index) {
-      ${_i(["r","c","d"],e)}
+      ${bi(["r","c","d"],e)}
       return ivec3(r, c, d);
     }
-  `}var QP=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=O_(t,n),a=z_(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=D_(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===tn.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===tn.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===tn.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===tn.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===tn.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=O_(n,r),s=z_(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=D_(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function eL(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function D_(e,t,n,r,a){let s=tL(t,r),i;if(a){let[l,u]=Nl(e[0],e[1]);i=l*u}else{let[l,u]=lc(e[0],e[1]);i=l*u}let o=eL(n,s);return i*o}function tL(e,t){switch(e){case tn.PACKED_2X2_FLOAT32:return Qm(t);case tn.PACKED_2X2_FLOAT16:return eA(t);case tn.UNPACKED_FLOAT32:return Zm(t);case tn.UNPACKED_FLOAT16:return Ym(t);case tn.PACKED_4X1_UNSIGNED_BYTE:return Jm(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function nL(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?tn.PACKED_2X2_FLOAT32:tn.UNPACKED_FLOAT32:e?tn.PACKED_2X2_FLOAT16:tn.UNPACKED_FLOAT16}function O_(e,t){if(e===Yn.UPLOAD)return tn.PACKED_2X2_FLOAT32;if(e===Yn.RENDER||e==null)return nL(t);if(e===Yn.DOWNLOAD||e===Yn.PIXELS)return tn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function z_(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Va=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+  `}var HP=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=zb(t,n),a=Pb(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=Ob(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===tn.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===tn.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===tn.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===tn.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===tn.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=zb(n,r),s=Pb(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=Ob(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],c=l.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function GP(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function Ob(e,t,n,r,a){let s=qP(t,r),i;if(a){let[l,c]=Il(e[0],e[1]);i=l*c}else{let[l,c]=uc(e[0],e[1]);i=l*c}let o=GP(n,s);return i*o}function qP(e,t){switch(e){case tn.PACKED_2X2_FLOAT32:return Qm(t);case tn.PACKED_2X2_FLOAT16:return eA(t);case tn.UNPACKED_FLOAT32:return Zm(t);case tn.UNPACKED_FLOAT16:return Ym(t);case tn.PACKED_4X1_UNSIGNED_BYTE:return Jm(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function XP(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?tn.PACKED_2X2_FLOAT32:tn.UNPACKED_FLOAT32:e?tn.PACKED_2X2_FLOAT16:tn.UNPACKED_FLOAT16}function zb(e,t){if(e===Yn.UPLOAD)return tn.PACKED_2X2_FLOAT32;if(e===Yn.RENDER||e==null)return XP(t);if(e===Yn.DOWNLOAD||e===Yn.PIXELS)return tn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function Pb(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Va=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       float unaryOperation(float x) {
         ${t}
       }
@@ -888,11 +888,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},wr="if (isnan(x)) return x;",rL="return x;",P_="return abs(x);",aL="return (x >= 0.0) ? x : (exp(x) - 1.0);",sL=wr+`
+    `}},wr="if (isnan(x)) return x;",KP="return x;",Lb="return abs(x);",ZP="return (x >= 0.0) ? x : (exp(x) - 1.0);",YP=wr+`
   return (x < 0.0) ? 0.0 : x;
-`,iL=wr+`
+`,JP=wr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,hp="return x;",oL="return x;",lL=`
+`,dp="return x;",QP="return x;",eL=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -901,7 +901,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,uL=`
+`,tL=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -911,7 +911,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,cL=`
+`,nL=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -932,17 +932,17 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},hL=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=mn("rc",t),r=ct(t),a=GP(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
+    `}},rL=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=mn("rc",t),r=ut(t),a=PP(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
       void main() {
         ${r} rc = getOutputCoords();
         vec4 packedInput = getA(${a});
 
         setOutput(getChannel(packedInput, ${i}));
       }
-    `}},dL=Wr.whereImpl,pL=1e-7,fL=1e-4,nA={};function mL(e){return e in nA||(nA[e]={}),nA[e]}var AL=128,yL=600;function gL(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*yL/1024/1024}var Rl=class extends iu{constructor(e){super();if(this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Vr(J().getNumber("WEBGL_VERSION"));this.binaryCache=mL(J().getNumber("WEBGL_VERSION")),this.gpgpu=new cp(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new QP(this.gpgpu),this.numMBBeforeWarning=gL(),this.texData=new wh(this,$r())}nextDataId(){return Rl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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:Yn.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,a){if(J().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:Yn.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new El(i,hp):h=new Va(i,hp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let c;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);c=R.mergeRealAndImagArrays(h,d)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new El(r,hp):p=new Va(r,hp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let p=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...uc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];c=R.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}u!=null&&this.disposeIntermediateTensorInfo(u);let h=this.convertAndCacheOnCPU(e,c),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&$r().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return We(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Lw(n))throw J().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...uc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?sp(t):t,o=s?new Rz(i):new Ez(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture,u.texShape[0],u.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=$r().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=AL){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return dL(e.shape,t)}packedUnaryOp(e,t,n){let r=new El(e.shape,t),a=this.compileAndRun(r,[e],n);return $r().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=F_(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,P_,e.dtype);let t=new Va(e.shape,P_),n=this.compileAndRun(t,[e]);return $r().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return $r().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new hL(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new ZP(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[gi(e.shape),...xi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[gi(t),...xi(t)],s=new $_(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=sp(r),i;n?i=new Cz(s):i=new Tz(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===oc.DENSE){let m=uc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!ic(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let u={shape:s.shape,texData:i,isUniform:!1},c=xP(e,l,u),h=this.getAndSaveBinary(c,()=>yP(this.gpgpu,e,l,u)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),gP(this.gpgpu,h,l,u,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=W(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(ve(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?pL:fL}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let c=t.texShape;if(c==null&&(c=t_(n,o),t.texShape=c),a!=null){let h=sp(n),d,p=c[1],f=c[0],m=a instanceof Uint8Array;o?([p,f]=Nl(c[0],c[1]),d=new Mz(h,[f,p],m)):d=new Fz(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Yn.PIXELS:this.texData.get(A.dataId).usage=Yn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-u)}else{let h=this.acquireTexture(c,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=xL(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Rl.nextDataId=0;function xL(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 ${t}`)}var L_="3.3.0";function W_(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}$u.isBrowser()&&il("webgl",()=>new Rl,2);var wL={forceHalfFloat:W_},B_=`
+    `}},aL=Wr.whereImpl,sL=1e-7,iL=1e-4,nA={};function oL(e){return e in nA||(nA[e]={}),nA[e]}var lL=128,uL=600;function cL(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*uL/1024/1024}var Rl=class extends ou{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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Vr(J().getNumber("WEBGL_VERSION"));this.binaryCache=oL(J().getNumber("WEBGL_VERSION")),this.gpgpu=new hp(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 HP(this.gpgpu),this.numMBBeforeWarning=cL(),this.texData=new bh(this,$r())}nextDataId(){return Rl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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:Yn.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,a){if(J().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:Yn.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new El(i,dp):h=new Va(i,dp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,c;l&&(c=v.now());let u;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);u=R.mergeRealAndImagArrays(h,d)}else u=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-c),this.convertAndCacheOnCPU(e,u)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new El(r,dp):p=new Va(r,dp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,c;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let p=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...cc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let u;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];u=R.mergeRealAndImagArrays(f,m)}else if(l==null)u=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);u=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}c!=null&&this.disposeIntermediateTensorInfo(c);let h=this.convertAndCacheOnCPU(e,u),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&$r().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return We(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Ww(n))throw J().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...cc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?ip(t):t,o=s?new vz(i):new _z(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),c=this.texData.get(l.dataId),u=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),u}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,c)=>({name:s[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=$r().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=lL){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return aL(e.shape,t)}packedUnaryOp(e,t,n){let r=new El(e.shape,t),a=this.compileAndRun(r,[e],n);return $r().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=Fb(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Lb,e.dtype);let t=new Va(e.shape,Lb),n=this.compileAndRun(t,[e]);return $r().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return $r().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new rL(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new VP(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[gi(e.shape),...xi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[gi(t),...xi(t)],s=new Db(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=ip(r),i;n?i=new bz(s):i=new wz(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===lc.DENSE){let m=cc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!oc(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let c={shape:s.shape,texData:i,isUniform:!1},u=hP(e,l,c),h=this.getAndSaveBinary(u,()=>uP(this.gpgpu,e,l,c)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),cP(this.gpgpu,h,l,c,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=L(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(ve(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?sL:iL}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,c;l&&(c=v.now());let u=t.texShape;if(u==null&&(u=nb(n,o),t.texShape=u),a!=null){let h=ip(n),d,p=u[1],f=u[0],m=a instanceof Uint8Array;o?([p,f]=Il(u[0],u[1]),d=new Iz(h,[f,p],m)):d=new kz(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Yn.PIXELS:this.texData.get(A.dataId).usage=Yn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-c)}else{let h=this.acquireTexture(u,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=hL(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Rl.nextDataId=0;function hL(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 Wb="3.3.0";function Bb(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}Du.isBrowser()&&il("webgl",()=>new Rl,2);var dL={forceHalfFloat:Bb},Vb=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,Fl=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
+`,Ml=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
       float binaryOperation(float a, float b) {
         ${e}
       }
@@ -952,17 +952,17 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float b = getBAtOutCoords();
         setOutput(binaryOperation(a, b));
       }
-    `}},dp=`
+    `}},pp=`
   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;
-`,hc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=R.assertAndGetBroadcastShape(t,n);let a=this.outputShape.length,s="";if(r)if(a===0||v.sizeFromShape(this.outputShape)===1)s=`
+`,dc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=R.assertAndGetBroadcastShape(t,n);let a=this.outputShape.length,s="";if(r)if(a===0||v.sizeFromShape(this.outputShape)===1)s=`
           result.y = 0.;
           result.z = 0.;
           result.w = 0.;
         `;else if(s=`
-          ${ct(a)} coords = getOutputCoords();
+          ${ut(a)} coords = getOutputCoords();
         `,a===1)s+=`
             result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
             result.z = 0.;
@@ -989,21 +989,21 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function zn(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 _L={kernelName:Ns,backendName:"webgl",kernelFunc:zn};function Ua(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=zn({inputs:{x:r},backend:n}),l=zn({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var bL={kernelName:Ch,backendName:"webgl",kernelFunc:Ua},V_="return (a < 0.) ? b * a : a;",U_=`
+    `}};function zn(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 pL={kernelName:Is,backendName:"webgl",kernelFunc:zn};function Ua(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=zn({inputs:{x:r},backend:n}),l=zn({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var fL={kernelName:Eh,backendName:"webgl",kernelFunc:Ua},Ub="return (a < 0.) ? b * a : a;",jb=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function vL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hc(U_,a.shape,i.shape):new Fl(V_,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var kL={kernelName:Is,backendName:"webgl",kernelFunc:vL},j_="return (a < 0.) ? b * a : a;",H_=`
+`;function mL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new dc(jb,a.shape,i.shape):new Ml(Ub,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var AL={kernelName:Ns,backendName:"webgl",kernelFunc:mL},Hb="return (a < 0.) ? b * a : a;",Gb=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function NL(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hc(H_,r.shape,a.shape):new Fl(j_,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var IL={kernelName:Ps,backendName:"webgl",kernelFunc:NL},G_="if (isnan(x)) return x;",SL=`
+`;function yL(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new dc(Gb,r.shape,a.shape):new Ml(Hb,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var gL={kernelName:Ps,backendName:"webgl",kernelFunc:yL},qb="if (isnan(x)) return x;",xL=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,TL=`
+`,wL=`
   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 Ze({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let u=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new El(i.shape,t):c=new Va(i.shape,e),o.runWebGLProgram(c,[i],l)}}function nn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,c=o;if(r&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[b,_]=w,x={dataId:b.dataId,dtype:b.dtype,shape:l.shape},I={dataId:_.dataId,dtype:_.dtype,shape:u.shape},S=new Fl(e,l.shape,u.shape);return c.runWebGLProgram(S,[x,I],ar(b.dtype,_.dtype))}),g=Ua({inputs:{real:A,imag:y},backend:c});return c.disposeIntermediateTensorInfo(A),c.disposeIntermediateTensorInfo(y),g}let h=s||ar(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&a!=null){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=a(l.shape,u.shape,f.values,m.values,h),g=c.makeTensorInfo(y,h),w=c.texData.get(g.dataId);return w.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new hc(t,l.shape,u.shape,n):p=new Fl(e,l.shape,u.shape),c.runWebGLProgram(p,[l,u],h)}}function pp(e,t=!1){if(e==="linear")return t?oL:rL;if(e==="relu")return t?uL:sL;if(e==="elu")return t?lL:aL;if(e==="relu6")return t?cL:iL;if(e==="prelu")return t?H_:j_;if(e==="leakyrelu")return t?U_:V_;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var q_=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let u=r?e[1]:e[2],c=Math.ceil(u/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
+`;function Ze({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let c=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return c?u=new El(i.shape,t):u=new Va(i.shape,e),o.runWebGLProgram(u,[i],l)}}function nn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:c}=i,u=o;if(r&&l.dtype==="complex64"){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[b,_]=w,x={dataId:b.dataId,dtype:b.dtype,shape:l.shape},N={dataId:_.dataId,dtype:_.dtype,shape:c.shape},T=new Ml(e,l.shape,c.shape);return u.runWebGLProgram(T,[x,N],ar(b.dtype,_.dtype))}),g=Ua({inputs:{real:A,imag:y},backend:u});return u.disposeIntermediateTensorInfo(A),u.disposeIntermediateTensorInfo(y),g}let h=s||ar(l.dtype,c.dtype);if(u.shouldExecuteOnCPU([l,c])&&a!=null){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=a(l.shape,c.shape,f.values,m.values,h),g=u.makeTensorInfo(y,h),w=u.texData.get(g.dataId);return w.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new dc(t,l.shape,c.shape,n):p=new Ml(e,l.shape,c.shape),u.runWebGLProgram(p,[l,c],h)}}function fp(e,t=!1){if(e==="linear")return t?QP:KP;if(e==="relu")return t?tL:YP;if(e==="elu")return t?eL:ZP;if(e==="relu6")return t?nL:JP;if(e==="prelu")return t?Gb:Hb;if(e==="leakyrelu")return t?jb:Ub;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var Xb=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let c=r?e[1]:e[2],u=Math.ceil(c/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${i}
         }`:l?m=`vec4 activation(vec4 a) {
@@ -1014,11 +1014,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",w="rc.x";e[0]<t[0]?g=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(w=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
       ${m}
 
-      const float sharedDimension = ${c}.0;
+      const float sharedDimension = ${u}.0;
 
       vec4 dot2x2ARowBCol(ivec3 rc) {
         vec4 result = vec4(0);
-        for (int i = 0; i < ${c}; i++) {
+        for (int i = 0; i < ${u}; i++) {
           int batchA = ${g};
           int batchB = ${w};
           vec4 a = getMatrixA(batchA, ${h});
@@ -1042,7 +1042,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}},X_={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},K_=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
+    `}},Kb={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Zb=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
       float binaryOpComplex(
           float areal, float aimag, float breal, float bimag) {
         ${e}
@@ -1055,7 +1055,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float bimag = getBImagAtOutCoords();
         setOutput(binaryOpComplex(areal, aimag, breal, bimag));
       }
-    `}},Z_="return a * b;";function Y_(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),u=new K_(X_.REAL,r.shape,a.shape),c=new K_(X_.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Ua({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[u,c]=DP(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(c,s),d=n.texData.get(h.dataId);return d.values=u,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new hc(Z_,r.shape,a.shape):i=new Fl(Z_,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var CL={kernelName:$s,backendName:"webgl",kernelFunc:Y_};function EL(e,t,n){let r=[gi(e.shape),...xi(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[gi(t),...xi(t)],i=new $_(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ye(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let c=i.texData.get(a.dataId);return c.isPacked&&!ic(a.shape,l)&&!(c.texture!==null&&ic(c.shape,l))?EL(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var RL={kernelName:Oo,backendName:"webgl",kernelFunc:ye},J_=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${v.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";a%n>0&&(u=`
+    `}},Yb="return a * b;";function Jb(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),c=new Zb(Kb.REAL,r.shape,a.shape),u=new Zb(Kb.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Ua({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[c,u]=SP(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(u,s),d=n.texData.get(h.dataId);return d.values=c,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new dc(Yb,r.shape,a.shape):i=new Ml(Yb,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var bL={kernelName:$s,backendName:"webgl",kernelFunc:Jb};function _L(e,t,n){let r=[gi(e.shape),...xi(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[gi(t),...xi(t)],i=new Db(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ye(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),c=v.sizeFromShape(l);v.assert(o===c,()=>`The new shape (${l}) has ${c} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let u=i.texData.get(a.dataId);return u.isPacked&&!oc(a.shape,l)&&!(u.texture!==null&&oc(u.shape,l))?_L(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var vL={kernelName:Oo,backendName:"webgl",kernelFunc:ye},Qb=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let u=1/t;l=`sumValue += dot(values * ${v.isInt(u)?u.toPrecision(2):u}, ones);`}let c="";a%n>0&&(c=`
         if (inIdx < 0 || inIdx >= ${a}) {
           return 0.0;
         }
@@ -1063,7 +1063,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
 
       float getValue(int batch, int inIdx) {
-        ${u}
+        ${c}
         return getX(batch, inIdx);
       }
 
@@ -1108,7 +1108,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(sumValue);
       }
-    `}},FL=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(n/4)*4,c=n%4,h=`
+    `}},kL=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,u=n%4,h=`
       if (${t==="sum"}) {
         sumValue += dot(values, ones);
       } else if (${t==="prod"}) {
@@ -1150,7 +1150,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float allValue = 1.0;
         float anyValue = 0.0;
 
-        for (int i = 0; i < ${u}; i += 4) {
+        for (int i = 0; i < ${c}; i += 4) {
           int inIdx = inOffset + i;
           ${d} values = ${d}(
             getValue(batch, inIdx),
@@ -1162,8 +1162,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           ${h}
         }
 
-        int inIdx = inOffset + ${u};
-        if (${c===1}) {
+        int inIdx = inOffset + ${c};
+        if (${u===1}) {
           ${d} values = ${d}(
             getValue(batch, inIdx),
             initializationValue,
@@ -1172,7 +1172,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           );
 
           ${h}
-        } else if (${c===2}) {
+        } else if (${u===2}) {
           ${d} values = ${d}(
             getValue(batch, inIdx),
             getValue(batch, inIdx + 1),
@@ -1181,7 +1181,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           );
 
           ${h}
-        } else if (${c===3}) {
+        } else if (${u===3}) {
           ${d} values = ${d}(
             getValue(batch, inIdx),
             getValue(batch, inIdx + 1),
@@ -1193,12 +1193,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(${l});
       }
-    `}};function ML(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=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function vi(e,t,n,r){let a=ML(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:u}=a[i],c,h;n==="mean"?c=i===0?new J_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new J_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):c=new FL({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},n),h=s,s=r.runWebGLProgram(c,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var DL=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=ct(this.rank),a=$L(t);this.userCode=`
+    `}};function IL(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=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function vi(e,t,n,r){let a=IL(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:c}=a[i],u,h;n==="mean"?u=i===0?new Qb({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},o):new Qb({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c}):u=new kL({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},n),h=s,s=r.runWebGLProgram(u,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var SL=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=ut(this.rank),a=NL(t);this.userCode=`
     void main() {
       ${r} resRC = getOutputCoords();
       setOutput(getA(${a}));
     }
-    `}};function $L(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var OL=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 ${this.rank} is not yet supported.`);let r=ct(this.rank),a=M_("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=a[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
+    `}};function NL(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var TL=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let c=0;c<n.length;c++)n[c]=e[t[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let r=ut(this.rank),a=$b("rc",this.rank),s=new Array(this.rank);for(let c=0;c<t.length;c++)s[t[c]]=a[c];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
     void main() {
       ${r} rc = getOutputCoords();
       vec4 result = vec4(0.);
@@ -1215,14 +1215,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       }
       setOutput(result);
     }
-    `}};function fp(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new OL(e.shape,t):new DL(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function zL(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),u=l!=null,c=e;u&&(c=fp(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(c.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=ye({inputs:{x:c},attrs:{shape:[m,f]},backend:r}),y=id(e.dtype),g=vi(A,y,"sum",r),w=ye({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),u&&r.disposeIntermediateTensorInfo(c),w}function rA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return zL(a,s,i,n)}var PL={kernelName:Xs,backendName:"webgl",kernelFunc:rA};function In(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let c=0;c<l.length;c++)l[c]=a.shape[s[c]];let u;if(i.shouldExecuteOnCPU([a])){let c=i.texData.get(a.dataId).values,h=tA(c,a.shape,a.dtype,s,l);u=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(u.dataId);d.values=h}else u=fp(a,s,i);return u}var LL={kernelName:Qs,backendName:"webgl",kernelFunc:In},Q_=1e3;function mp({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,h=n?e.shape[u-2]:e.shape[u-1],d=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),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(u>=2&&c>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let b=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],I=ye({inputs:{x:e},backend:a,attrs:{shape:_}}),S=ye({inputs:{x:t},backend:a,attrs:{shape:x}}),T=[I,S],M=Math.max(y,g),D=n?I.shape[1]:I.shape[2],z=s!=null,B=i!=null,U=l==="leakyrelu",j=l!=null?pp(l,!0):null,X=z||B||U||j!=null,H;if((p===1||f===1)&&D>Q_&&X===!1){let Y=I,ae=S;n&&(Y=In({inputs:{x:I},backend:a,attrs:{perm:[0,2,1]}}),T.push(Y)),r&&(ae=In({inputs:{x:S},backend:a,attrs:{perm:[0,2,1]}}),T.push(ae));let te=f!==1,ie=f===1,Q=Y;te&&(Q=ye({inputs:{x:Y},backend:a,attrs:{shape:[M,D,1]}}),T.push(Q));let he=f===1?2:1,le=ae;ie&&(le=ye({inputs:{x:ae},backend:a,attrs:{shape:[M,1,D]}}),T.push(le));let fe=Y_({inputs:{a:Q,b:le},backend:a});H=rA({inputs:{x:fe},backend:a,attrs:{axis:he,keepDims:!0}}),T.push(fe)}else{let Y=ar(e.dtype,t.dtype),ae=new q_(_,x,[M,p,f],n,r,z,j,B,U),te=[I,S];if(s!=null&&te.push(s),B&&te.push(i),U){let ie=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));te.push(ie),T.push(ie)}H=a.runWebGLProgram(ae,te,Y)}let ee=ye({inputs:{x:H},backend:a,attrs:{shape:b}});T.push(H);for(let Y of T)a.disposeIntermediateTensorInfo(Y);return ee}function WL(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:h}=r;return mp({a,b:s,transposeA:l,transposeB:u,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:c})}var BL={kernelName:ei,backendName:"webgl",kernelFunc:WL},eb="return abs(x);";function VL(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=F_(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new El(r.shape,eb):a=new Va(r.shape,eb),n.runWebGLProgram(a,[r],r.dtype)}var UL={kernelName:Yi,backendName:"webgl",kernelFunc:VL},jL=wr+`
+    `}};function mp(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new TL(e.shape,t):new SL(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function CL(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),c=l!=null,u=e;c&&(u=mp(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(u.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=ye({inputs:{x:u},attrs:{shape:[m,f]},backend:r}),y=od(e.dtype),g=vi(A,y,"sum",r),w=ye({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),c&&r.disposeIntermediateTensorInfo(u),w}function rA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return CL(a,s,i,n)}var EL={kernelName:Xs,backendName:"webgl",kernelFunc:rA};function Nn(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let u=0;u<l.length;u++)l[u]=a.shape[s[u]];let c;if(i.shouldExecuteOnCPU([a])){let u=i.texData.get(a.dataId).values,h=tA(u,a.shape,a.dtype,s,l);c=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(c.dataId);d.values=h}else c=mp(a,s,i);return c}var RL={kernelName:Qs,backendName:"webgl",kernelFunc:Nn},e_=1e3;function Ap({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let c=e.shape.length,u=t.shape.length,h=n?e.shape[c-2]:e.shape[c-1],d=r?t.shape[u-1]:t.shape[u-2],p=n?e.shape[c-1]:e.shape[c-2],f=r?t.shape[u-2]:t.shape[u-1],m=e.shape.slice(0,-2),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(c>=2&&u>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let b=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],N=ye({inputs:{x:e},backend:a,attrs:{shape:_}}),T=ye({inputs:{x:t},backend:a,attrs:{shape:x}}),C=[N,T],F=Math.max(y,g),z=n?N.shape[1]:N.shape[2],B=s!=null,V=i!=null,U=l==="leakyrelu",j=l!=null?fp(l,!0):null,X=B||V||U||j!=null,G;if((p===1||f===1)&&z>e_&&X===!1){let Y=N,ae=T;n&&(Y=Nn({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),C.push(Y)),r&&(ae=Nn({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),C.push(ae));let te=f!==1,oe=f===1,Q=Y;te&&(Q=ye({inputs:{x:Y},backend:a,attrs:{shape:[F,z,1]}}),C.push(Q));let he=f===1?2:1,le=ae;oe&&(le=ye({inputs:{x:ae},backend:a,attrs:{shape:[F,1,z]}}),C.push(le));let fe=Jb({inputs:{a:Q,b:le},backend:a});G=rA({inputs:{x:fe},backend:a,attrs:{axis:he,keepDims:!0}}),C.push(fe)}else{let Y=ar(e.dtype,t.dtype),ae=new Xb(_,x,[F,p,f],n,r,B,j,V,U),te=[N,T];if(s!=null&&te.push(s),V&&te.push(i),U){let oe=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));te.push(oe),C.push(oe)}G=a.runWebGLProgram(ae,te,Y)}let ee=ye({inputs:{x:G},backend:a,attrs:{shape:b}});C.push(G);for(let Y of C)a.disposeIntermediateTensorInfo(Y);return ee}function ML(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:c,activation:u,leakyreluAlpha:h}=r;return Ap({a,b:s,transposeA:l,transposeB:c,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:u})}var FL={kernelName:ei,backendName:"webgl",kernelFunc:ML},t_="return abs(x);";function $L(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=Fb(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new El(r.shape,t_):a=new Va(r.shape,t_),n.runWebGLProgram(a,[r],r.dtype)}var DL={kernelName:Yi,backendName:"webgl",kernelFunc:$L},OL=wr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return acos(x);
-`,HL=Ze({opSnippet:jL}),GL={kernelName:Ji,backendName:"webgl",kernelFunc:HL},qL=wr+`
+`,zL=Ze({opSnippet:OL}),PL={kernelName:Ji,backendName:"webgl",kernelFunc:zL},LL=wr+`
   if (x < 1.0) return NAN;
-return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,backendName:"webgl",kernelFunc:XL},tb="return a + b;",ZL=nn({opSnippet:tb,packedOpSnippet:tb,supportsComplex:!0,cpuKernelImpl:wP}),YL={kernelName:Ia,backendName:"webgl",kernelFunc:ZL},JL=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+return log(x + sqrt(x * x - 1.0));`,WL=Ze({opSnippet:LL}),BL={kernelName:Qi,backendName:"webgl",kernelFunc:WL},n_="return a + b;",VL=nn({opSnippet:n_,packedOpSnippet:n_,supportsComplex:!0,cpuKernelImpl:dP}),UL={kernelName:Na,backendName:"webgl",kernelFunc:VL},jL=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1230,7 +1230,7 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
         float result = ${r};
         setOutput(result);
       }
-    `}},QL=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+    `}},HL=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1238,7 +1238,7 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
         vec4 result = ${r};
         setOutput(result);
       }
-    `}};function Ap(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return zn({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=Ap({inputs:r.slice(0,o),backend:n}),u=Ap({inputs:r.slice(o),backend:n});return Ap({inputs:[l,u],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>ar(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new QL(r[0].shape,s):new JL(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var eW={kernelName:ls,backendName:"webgl",kernelFunc:Ap};function tW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("all",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var nW={kernelName:kh,backendName:"webgl",kernelFunc:tW};function rW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("any",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var aW={kernelName:Nh,backendName:"webgl",kernelFunc:rW},sW=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
+    `}};function yp(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return zn({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=yp({inputs:r.slice(0,o),backend:n}),c=yp({inputs:r.slice(o),backend:n});return yp({inputs:[l,c],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>ar(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new HL(r[0].shape,s):new jL(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var GL={kernelName:ls,backendName:"webgl",kernelFunc:yp};function qL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=Nn({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("all",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var XL={kernelName:Ih,backendName:"webgl",kernelFunc:qL};function KL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=Nn({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("any",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var ZL={kernelName:Nh,backendName:"webgl",kernelFunc:KL},YL=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
@@ -1258,23 +1258,23 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
         }
         setOutput(float(bestIndex));
       }
-    `}},iW=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ct(o),u=mn("coords",o),c,h;if(s===1){h=o+1;let I=ct(h);c=`
-        ${I} sourceLocR = ${I}(${u.join()}, 0);
-        ++${u[o-1]};
-        ${I} sourceLocG = ${I}(${u.join()}, 0);
-        ++${u[o-2]};
-        ${I} sourceLocA = ${I}(${u.join()}, 0);
-        --${u[o-1]};
-        ${I} sourceLocB = ${I}(${u.join()}, 0);
-        --${u[o-2]};`}else h=o,c=`
+    `}},JL=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ut(o),c=mn("coords",o),u,h;if(s===1){h=o+1;let N=ut(h);u=`
+        ${N} sourceLocR = ${N}(${c.join()}, 0);
+        ++${c[o-1]};
+        ${N} sourceLocG = ${N}(${c.join()}, 0);
+        ++${c[o-2]};
+        ${N} sourceLocA = ${N}(${c.join()}, 0);
+        --${c[o-1]};
+        ${N} sourceLocB = ${N}(${c.join()}, 0);
+        --${c[o-2]};`}else h=o,u=`
         ${l} sourceLocR = coords;
-        ++${u[o-1]};
+        ++${c[o-1]};
         ${l} sourceLocG = coords;
-        ++${u[o-2]};
+        ++${c[o-2]};
         ${l} sourceLocA = coords;
-        --${u[o-1]};
+        --${c[o-1]};
         ${l} sourceLocB = coords;
-        --${u[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(I=>"int "+I),m=mn("sourceLocR",h-1).concat("inIdx.r"),A=mn("sourceLocG",h-1).concat("inIdx.g"),y=mn("sourceLocB",h-1).concat("inIdx.b"),g=mn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",b=r?"":`
+        --${c[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=mn("sourceLocR",h-1).concat("inIdx.r"),A=mn("sourceLocG",h-1).concat("inIdx.g"),y=mn("sourceLocB",h-1).concat("inIdx.b"),g=mn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",b=r?"":`
           inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
                              getBestIndicesAChannel(${A.join()}),
                              getBestIndicesAChannel(${y.join()}),
@@ -1294,9 +1294,9 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
       ${x}
       void main() {
         ${l} coords = getOutputCoords();
-        bool hasNextCol = ${u[o-1]} < ${i[o-1]-1};
-        bool hasNextRow = ${u[o-2]} < ${i[o-2]-1};
-        ${c}
+        bool hasNextCol = ${c[o-1]} < ${i[o-1]-1};
+        bool hasNextRow = ${c[o-2]} < ${i[o-2]-1};
+        ${u}
         ivec4 srcIdx = ivec4(sourceLocR${p}, sourceLocG${p},
           sourceLocB${p}, sourceLocA${p}) * ${t};
         ivec4 inIdx = srcIdx;
@@ -1320,23 +1320,23 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
         }
         setOutput(bestIndex);
       }
-    `}};function nb(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new sW(o,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 h=nb(e,t,n,c);return e.disposeIntermediateTensorInfo(c),h}function rb(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new iW(a,i,n,r==null),l=r==null?[t]:[t,r],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let c=rb(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function ab(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),u=ye({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(u);let c=nb(e,u,r);s.push(c);let h=ye({inputs:{x:c},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return rb(e,t,r)}function oW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let c=ab(n,l,i[0],"max");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var lW={kernelName:us,backendName:"webgl",kernelFunc:oW};function uW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let c=ab(n,l,i[0],"min");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var cW={kernelName:uu,backendName:"webgl",kernelFunc:uW},hW=wr+`
+    `}};function r_(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new YL(o,n,r==null),c=[t];r!=null&&c.push(r);let u=e.runWebGLProgram(l,c,"int32");if(u.shape[1]===1)return u;let h=r_(e,t,n,u);return e.disposeIntermediateTensorInfo(u),h}function a_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new JL(a,i,n,r==null),l=r==null?[t]:[t,r],c=e.runWebGLProgram(o,l,"int32");if(c.shape.length===t.shape.length){let u=a_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),u}return c}function s_(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),c=ye({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(c);let u=r_(e,c,r);s.push(u);let h=ye({inputs:{x:u},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return a_(e,t,r)}function QL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=Nn({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=s_(n,l,i[0],"max");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var eW={kernelName:us,backendName:"webgl",kernelFunc:QL};function tW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=Nn({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=s_(n,l,i[0],"min");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var nW={kernelName:cu,backendName:"webgl",kernelFunc:tW},rW=wr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return asin(x);
-`,dW=Ze({opSnippet:hW}),pW={kernelName:eo,backendName:"webgl",kernelFunc:dW},fW=wr+"return log(x + sqrt(x * x + 1.0));",mW=Ze({opSnippet:fW}),AW={kernelName:to,backendName:"webgl",kernelFunc:mW},yW=wr+`
+`,aW=Ze({opSnippet:rW}),sW={kernelName:eo,backendName:"webgl",kernelFunc:aW},iW=wr+"return log(x + sqrt(x * x + 1.0));",oW=Ze({opSnippet:iW}),lW={kernelName:to,backendName:"webgl",kernelFunc:oW},uW=wr+`
   return atan(x);
-`,gW=Ze({opSnippet:yW}),xW={kernelName:no,backendName:"webgl",kernelFunc:gW},wW=SL+`
+`,cW=Ze({opSnippet:uW}),hW={kernelName:no,backendName:"webgl",kernelFunc:cW},dW=xL+`
   return atan(a, b);
-`,_W=`
+`,pW=`
   vec4 result = atan(a, b);
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+TL+`
+  `+wL+`
   return result;
-`,bW=nn({opSnippet:wW,packedOpSnippet:_W}),vW={kernelName:ao,backendName:"webgl",kernelFunc:bW},kW=wr+`
+`,fW=nn({opSnippet:dW,packedOpSnippet:pW}),mW={kernelName:ao,backendName:"webgl",kernelFunc:fW},AW=wr+`
   if ((x < -1.0) || (x > 1.0)) return NAN;
-return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelName:ro,backendName:"webgl",kernelFunc:NW},dc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let I=">=";this.userCode=`
+return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,yW=Ze({opSnippet:AW}),gW={kernelName:ro,backendName:"webgl",kernelFunc:yW},pc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=`
         const ivec2 strides = ivec2(${i}, ${o});
         const ivec2 pads = ivec2(${d}, ${p});
 
@@ -1356,7 +1356,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           int minMaxPosition = 0;
           float avgValue = 0.0;
 
-          for (int wR = 0; wR < ${c};
+          for (int wR = 0; wR < ${u};
               wR += ${l}) {
             int xR = xRCorner + wR;
 
@@ -1365,7 +1365,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             }
 
             for (int wC = 0; wC < ${h};
-                wC += ${u}) {
+                wC += ${c}) {
               int xC = xCCorner + wC;
 
               if (xC < 0 || xC >= ${e.inWidth}) {
@@ -1378,7 +1378,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
               // use the current value.
               float currMinMaxValue = mix(
                   value, minMaxValue, minMaxValueFound);
-              if (value ${I} currMinMaxValue) {
+              if (value ${N} currMinMaxValue) {
                 minMaxValue = value;
                 minMaxValueFound = 1.0;
                 minMaxPosition = ${r?a?m:A:`wR * ${h} + wC`};
@@ -1424,7 +1424,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         float avgValue = 0.0;
         count = 0.0;
 
-        for (int wR = 0; wR < ${c};
+        for (int wR = 0; wR < ${u};
             wR += ${l}) {
           int xR = xRCorner + wR;
 
@@ -1433,13 +1433,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
 
           for (int wC = 0; wC < ${b}; wC += 4) {
-            int xC = xCCorner + wC * ${u};
+            int xC = xCCorner + wC * ${c};
 
             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)
+              getValue(batch, xR, xC + ${c}, d),
+              getValue(batch, xR, xC + 2 * ${c}, d),
+              getValue(batch, xR, xC + 3 * ${c}, d)
             );
 
             ${x}
@@ -1458,7 +1458,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           } else if (${_===2}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
-              getValue(batch, xR, xC + ${u}, d),
+              getValue(batch, xR, xC + ${c}, d),
               initializationValue,
               initializationValue
             );
@@ -1467,8 +1467,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           } else if (${_===3}) {
             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 + ${c}, d),
+              getValue(batch, xR, xC + 2 * ${c}, d),
               initializationValue
             );
 
@@ -1477,7 +1477,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(${w});
       }
-    `}},aA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,c=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let T=">=";this.userCode=`
+    `}},aA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,c=e.dilationDepth,u=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let C=">=";this.userCode=`
         const ivec3 strides =
             ivec3(${i}, ${o}, ${l});
         const ivec3 pads = ivec3(${m}, ${A}, ${y});
@@ -1499,7 +1499,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           int minMaxPosition = 0;
 
           for (int wD = 0; wD < ${d};
-              wD += ${u}) {
+              wD += ${c}) {
             int xD = xDCorner + wD;
 
             if (xD < 0 || xD >= ${e.inDepth}) {
@@ -1507,7 +1507,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             }
 
             for (int wR = 0; wR < ${p};
-                wR += ${c}) {
+                wR += ${u}) {
               int xR = xRCorner + wR;
 
               if (xR < 0 || xR >= ${e.inHeight}) {
@@ -1528,7 +1528,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 // use the current value.
                 float currMinMaxValue = mix(
                     value, minMaxValue, minMaxValueFound);
-                if (value ${T} currMinMaxValue) {
+                if (value ${C} currMinMaxValue) {
                   minMaxValue = value;
                   minMaxValueFound = 1.0;
                   minMaxPosition = ${r?a?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${p} * ${f} +
@@ -1539,7 +1539,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let b="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,I=s%4,S=`
+      `;return}let b="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,T=`
       if (${g}) {
         avgValue += dot(values, ones);
       } else {
@@ -1579,7 +1579,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         count = 0.0;
 
         for (int wD = 0; wD < ${d};
-            wD += ${u}) {
+            wD += ${c}) {
           int xD = xDCorner + wD;
 
           if (xD < 0 || xD >= ${e.inDepth}) {
@@ -1587,7 +1587,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
 
           for (int wR = 0; wR < ${p};
-            wR += ${c}) {
+            wR += ${u}) {
             int xR = xRCorner + wR;
 
             if (xR < 0 || xR >= ${e.inHeight}) {
@@ -1604,11 +1604,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 getValue(batch, xD, xR, xC + 3 * ${h}, ch)
               );
 
-              ${S}
+              ${T}
             }
 
             int xC = xCCorner + ${x};
-            if (${I===1}) {
+            if (${N===1}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
                 initializationValue,
@@ -1616,8 +1616,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 initializationValue
               );
 
-              ${S}
-            } else if (${I===2}) {
+              ${T}
+            } else if (${N===2}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
                 getValue(batch, xD, xR, xC + ${h}, ch),
@@ -1625,8 +1625,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 initializationValue
               );
 
-              ${S}
-            } else if (${I===3}) {
+              ${T}
+            } else if (${N===3}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
                 getValue(batch, xD, xR, xC + ${h}, ch),
@@ -1634,14 +1634,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 initializationValue
               );
 
-              ${S}
+              ${T}
             }
           }
           setOutput(${_});
         }
       }
-    `}};function SW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return zn({inputs:{x:a},backend:n});let h=new dc(c,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var TW={kernelName:cs,backendName:"webgl",kernelFunc:SW};function CW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,l,u),d=new aA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var EW={kernelName:cu,backendName:"webgl",kernelFunc:CW},RW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,c=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
-      const ivec2 pads = ivec2(${u}, ${c});
+    `}};function xW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return zn({inputs:{x:a},backend:n});let h=new pc(u,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var wW={kernelName:cs,backendName:"webgl",kernelFunc:xW};function bW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,l,c),d=new aA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var _W={kernelName:hu,backendName:"webgl",kernelFunc:bW},vW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,c=o-1-e.padInfo.top,u=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
+      const ivec2 pads = ivec2(${c}, ${u});
       const float avgMultiplier = float(${h});
 
       void main() {
@@ -1682,7 +1682,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},FW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=c-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
+    `}},kW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=u-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
       const ivec3 pads = ivec3(${p}, ${f}, ${m});
       const float avgMultiplier = float(${A});
 
@@ -1701,7 +1701,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         // ? = to be determined. : = across all values in that axis.
         float dotProd = 0.0;
 
-        for (int wD = 0; wD < ${c};
+        for (int wD = 0; wD < ${u};
             wD += ${o}) {
           float dyD = float(dyDCorner + wD) / ${a}.0;
 
@@ -1721,7 +1721,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             int idyR = int(dyR);
 
             for (int wC = 0; wC < ${d};
-                wC += ${u}) {
+                wC += ${c}) {
               float dyC = float(dyCCorner + wC) / ${i}.0;
 
               if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
@@ -1738,7 +1738,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function MW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new FW(d);return n.runWebGLProgram(p,[a],i.dtype)}var $W={kernelName:Sh,backendName:"webgl",kernelFunc:MW};function DW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;kl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=r,c=R.computePool2DInfo(i.shape,o,l,1,u),h=new RW(c);return n.runWebGLProgram(h,[a],i.dtype)}var OW={kernelName:Ih,backendName:"webgl",kernelFunc:DW};function zW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return mp({a,b:s,transposeA:i,transposeB:o,backend:n})}var PW={kernelName:hs,backendName:"webgl",kernelFunc:zW},LW=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};function IW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new kW(d);return n.runWebGLProgram(p,[a],i.dtype)}var NW={kernelName:Th,backendName:"webgl",kernelFunc:IW};function SW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;kl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=new vW(u);return n.runWebGLProgram(h,[a],i.dtype)}var TW={kernelName:Sh,backendName:"webgl",kernelFunc:SW};function CW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return Ap({a,b:s,transposeA:i,transposeB:o,backend:n})}var EW={kernelName:hs,backendName:"webgl",kernelFunc:CW},RW=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         float x = getXAtOutCoords();
         float mean = getMeanAtOutCoords();
@@ -1748,7 +1748,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         float inv = scale * inversesqrt(variance + float(${s}));
         setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
       }
-    `}},WW=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}},MW=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         vec4 offset = ${i};
         vec4 scale = ${o};
@@ -1761,7 +1761,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         setOutput((x - mean) * inv + offset);
       }
-    `}},BW=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[r,a,s],c=null;i!=null&&(c=i.shape,u.push(i));let h=null;o!=null&&(h=o.shape,u.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new WW(r.shape,a.shape,s.shape,c,h,l):new LW(r.shape,a.shape,s.shape,c,h,l);return t.runWebGLProgram(d,u,u[0].dtype)},VW={kernelName:vs,backendName:"webgl",kernelFunc:BW},jW=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ct(this.rank),n=`uniform int start[${this.rank}];`,r=UW(this.rank),a,s=e.map((i,o)=>`sourceLoc.${sA[o]} = start[${o}] + coords.${sA[o]};`);a=`
+    `}},FW=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let c=[r,a,s],u=null;i!=null&&(u=i.shape,c.push(i));let h=null;o!=null&&(h=o.shape,c.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new MW(r.shape,a.shape,s.shape,u,h,l):new RW(r.shape,a.shape,s.shape,u,h,l);return t.runWebGLProgram(d,c,c[0].dtype)},$W={kernelName:vs,backendName:"webgl",kernelFunc:FW},OW=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ut(this.rank),n=`uniform int start[${this.rank}];`,r=DW(this.rank),a,s=e.map((i,o)=>`sourceLoc.${sA[o]} = start[${o}] + coords.${sA[o]};`);a=`
         ${t} sourceLoc;
         ${t} coords = getOutputCoords();
         ${s.join(`
@@ -1772,7 +1772,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${a}
         setOutput(getSource(${r}));
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},sA=["x","y","z","w","u","v"];function UW(e){if(e===1)return"sourceLoc";if(e<=6)return sA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var HW=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ct(this.rank),n=mn("coords",this.rank),r=mn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${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)}}},sA=["x","y","z","w","u","v"];function DW(e){if(e===1)return"sourceLoc";if(e<=6)return sA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var zW=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ut(this.rank),n=mn("coords",this.rank),r=mn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
       result.x = ${s};
       if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
         ++${r[this.rank-1]};
@@ -1790,7 +1790,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
       }
     `,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(`
+            ${t}(${e.map((c,u)=>`start[${u}]`).join()});`:e.map((c,u)=>`${r[u]} = ${n[u]} + start[${u}];`).join(`
 `);this.userCode=`
       uniform int start[${this.rank}];
       void main() {
@@ -1802,7 +1802,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${o}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function GW(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=cn.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function pc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=cn.parseSliceParams(a,s,i);if(cn.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=WP(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:u}=n.texData.get(a.dataId),c=cn.isSliceContinous(a.shape,o,l);if(u||!c){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new HW(l):new jW(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),GW(a,o,l,n)}var qW={kernelName:Wo,backendName:"webgl",kernelFunc:pc},XW=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=R.getReshaped(a.shape,s,o),u=R.getPermuted(l.length,s.length),c=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(c,i,s.length),p=[],f=ye({inputs:{x:a},backend:n,attrs:{shape:l}}),m=In({inputs:{x:f},backend:n,attrs:{perm:u}}),A=ye({inputs:{x:m},backend:n,attrs:{shape:c}}),y=pc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},KW={kernelName:hu,backendName:"webgl",kernelFunc:XW};function ZW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),u=R_(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var YW={kernelName:Th,backendName:"webgl",kernelFunc:ZW},JW="return float(a != b);",sb=nn({opSnippet:JW,dtype:"bool"}),QW={kernelName:To,backendName:"webgl",kernelFunc:sb};function fc(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return zn({inputs:{x:a.complexTensorInfos.real},backend:n})}var eB={kernelName:Kh,backendName:"webgl",kernelFunc:fc},tB="return float(int(x));";function nB(e,t){let n=new Va(e.shape,tB),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function iA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return zn({inputs:{x:a},backend:n});let i=Ft(a.shape),o=iA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Ua({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=fc({inputs:{input:a},backend:n}),o=iA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=zn({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return nB(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=sb({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var rB={kernelName:ds,backendName:"webgl",kernelFunc:iA},ib="return ceil(x);",aB=Ze({opSnippet:ib,packedOpSnippet:ib,cpuKernelImpl:bP}),sB={kernelName:ps,backendName:"webgl",kernelFunc:aB},iB=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${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 PW(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=cn.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function fc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=cn.parseSliceParams(a,s,i);if(cn.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=MP(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:c}=n.texData.get(a.dataId),u=cn.isSliceContinous(a.shape,o,l);if(c||!u){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new zW(l):new OW(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),PW(a,o,l,n)}var LW={kernelName:Wo,backendName:"webgl",kernelFunc:fc},WW=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=[],f=ye({inputs:{x:a},backend:n,attrs:{shape:l}}),m=Nn({inputs:{x:f},backend:n,attrs:{perm:c}}),A=ye({inputs:{x:m},backend:n,attrs:{shape:u}}),y=fc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},BW={kernelName:du,backendName:"webgl",kernelFunc:WW};function VW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),c=Mb(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var UW={kernelName:Ch,backendName:"webgl",kernelFunc:VW},jW="return float(a != b);",i_=nn({opSnippet:jW,dtype:"bool"}),HW={kernelName:To,backendName:"webgl",kernelFunc:i_};function mc(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return zn({inputs:{x:a.complexTensorInfos.real},backend:n})}var GW={kernelName:Zh,backendName:"webgl",kernelFunc:mc},qW="return float(int(x));";function XW(e,t){let n=new Va(e.shape,qW),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function iA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return zn({inputs:{x:a},backend:n});let i=Mt(a.shape),o=iA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Ua({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=mc({inputs:{input:a},backend:n}),o=iA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=zn({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return XW(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=i_({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var KW={kernelName:ds,backendName:"webgl",kernelFunc:iA},o_="return ceil(x);",ZW=Ze({opSnippet:o_,packedOpSnippet:o_,cpuKernelImpl:fP}),YW={kernelName:ps,backendName:"webgl",kernelFunc:ZW},JW=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1815,7 +1815,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         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)}}},oB=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
+    `}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)}}},QW=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1829,7 +1829,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         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 lB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new oB(a.shape):o=new iB(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var uB={kernelName:Sa,backendName:"webgl",kernelFunc:lB},cB=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
+    `}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 eB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new QW(a.shape):o=new JW(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var tB={kernelName:Sa,backendName:"webgl",kernelFunc:eB},nB=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
       void main() {
         float re = abs(getRealAtOutCoords());
         float im = abs(getImagAtOutCoords());
@@ -1842,7 +1842,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
         );
       }
-    `}};function ob(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function hB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new cB(r.shape),i=[ob(r,a.complexTensorInfos.real),ob(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var dB={kernelName:du,backendName:"webgl",kernelFunc:hB},pB=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
+    `}};function l_(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function rB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new nB(r.shape),i=[l_(r,a.complexTensorInfos.real),l_(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var aB={kernelName:pu,backendName:"webgl",kernelFunc:rB},sB=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int yR = coords.x;
@@ -1851,18 +1851,18 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${n.join(`
         `)}
       }
-    `}},fB=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ct(r),s=mn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],u=i.slice(-2),c=i.join(),h=`if (${l} < ${o[0]}) {
+    `}},iB=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ut(r),s=mn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],c=i.slice(-2),u=i.join(),h=`if (${l} < ${o[0]}) {
         return getChannel(
-            getT0(${c}), vec2(${u.join()}));
+            getT0(${u}), vec2(${c.join()}));
         }`;for(let f=1;f<o.length;f++){let m=o[f-1];h+=`
         if (${l} < ${o[f]}  && ${l} >= ${o[f-1]}) {
           return getChannel(
-            getT${f}(${yp(i,l,m)}),
-            vec2(${yp(u,l,m)}));
+            getT${f}(${gp(i,l,m)}),
+            vec2(${gp(c,l,m)}));
         }`}let d=o.length,p=o[o.length-1];h+=`
         return getChannel(
-          getT${d}(${yp(i,l,p)}),
-          vec2(${yp(u,l,p)}));`,this.userCode=`
+          getT${d}(${gp(i,l,p)}),
+          vec2(${gp(c,l,p)}));`,this.userCode=`
       float getValue(${i.map(f=>"int "+f)}) {
         ${h}
       }
@@ -1888,7 +1888,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(result);
       }
-    `}};function yp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function gp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return zn({inputs:{x:a.complexTensorInfos.imag},backend:n})}var mB={kernelName:Vh,backendName:"webgl",kernelFunc:gp};function Ml(e,t,n){let r=e[0].dtype;if(r==="complex64"){let u=e.map(f=>fc({inputs:{input:f},backend:n})),c=e.map(f=>gp({inputs:{input:f},backend:n})),h=Ml(u,t,n),d=Ml(c,t,n),p=Ua({inputs:{real:h,imag:d},backend:n});return u.forEach(f=>n.disposeIntermediateTensorInfo(f)),c.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:u,outShape:c}=lb(e,t,n),h=u.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=u[0].shape[0]===1,p=vP(h,c,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return u.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(e.length/2),c=Ml(e.slice(0,u),t,n),h=Ml(e.slice(u),t,n),d=Ml([c,h],t,n);return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let u=new fB(e.map(c=>c.shape),t);return n.runWebGLProgram(u,e,r)}let{tensors2D:a,outShape:s}=lb(e,t,n),i=new pB(a.map(u=>u.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(u=>n.disposeIntermediateTensorInfo(u));let l=ye({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function lb(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ye({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function ub(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(u=>v.sizeFromShape(u.shape)>0);if(o.length===1)return zn({inputs:{x:o[0]},backend:n});let l=o.map(u=>u.shape);return R.assertParamsConsistent(l,s),Ml(o,s,n)}var AB={kernelName:so,backendName:"webgl",kernelFunc:ub},cb=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,w="",b="";n&&(r?w=`float activation(float a) {
+    `}};function gp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function xp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return zn({inputs:{x:a.complexTensorInfos.imag},backend:n})}var oB={kernelName:Uh,backendName:"webgl",kernelFunc:xp};function Fl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let c=e.map(f=>mc({inputs:{input:f},backend:n})),u=e.map(f=>xp({inputs:{input:f},backend:n})),h=Fl(c,t,n),d=Fl(u,t,n),p=Ua({inputs:{real:h,imag:d},backend:n});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),u.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:c,outShape:u}=u_(e,t,n),h=c.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=c[0].shape[0]===1,p=mP(h,u,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),u=Fl(e.slice(0,c),t,n),h=Fl(e.slice(c),t,n),d=Fl([u,h],t,n);return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new iB(e.map(u=>u.shape),t);return n.runWebGLProgram(c,e,r)}let{tensors2D:a,outShape:s}=u_(e,t,n),i=new sB(a.map(c=>c.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let l=ye({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function u_(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ye({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function c_(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(c=>c.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(c=>v.sizeFromShape(c.shape)>0);if(o.length===1)return zn({inputs:{x:o[0]},backend:n});let l=o.map(c=>c.shape);return R.assertParamsConsistent(l,s),Fl(o,s,n)}var lB={kernelName:so,backendName:"webgl",kernelFunc:c_},h_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,c=e.dilationHeight,u=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,w="",b="";n&&(r?w=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?w=`float activation(float a) {
@@ -1918,14 +1918,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         // ? = to be determined. : = across all values in that axis.
         float dotProd = 0.0;
         for (int wR = 0; wR < ${h}; wR++) {
-          int xR = xRCorner + wR * ${u};
+          int xR = xRCorner + wR * ${c};
 
           if (xR < 0 || xR >= ${e.inHeight}) {
             continue;
           }
 
           for (int wC = 0; wC < ${d}; wC++) {
-            int xC = xCCorner + wC * ${c};
+            int xC = xCCorner + wC * ${u};
 
             if (xC < 0 || xC >= ${e.inWidth}) {
               continue;
@@ -2022,7 +2022,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${b}
         setOutput(result);
       }
-    `}},yB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
+    `}},uB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
       const ivec3 strides = ivec3(${a}, ${s}, ${i});
       const ivec3 pads = ivec3(${t}, ${n}, ${r});
 
@@ -2040,7 +2040,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         // 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++) {
+        for (int wF = 0; wF < ${u}; wF++) {
           int xF = xFCorner + wF * ${o};
 
           if (xF < 0 || xF >= ${e.inDepth}) {
@@ -2055,7 +2055,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             }
 
             for (int wC = 0; wC < ${d}; wC++) {
-              int xC = xCCorner + wC * ${u};
+              int xC = xCCorner + wC * ${c};
 
               if (xC < 0 || xC >= ${e.inWidth}) {
                 continue;
@@ -2110,18 +2110,18 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},gB=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:u,dilationHeight:c,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=fn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let b=0;b<=1;b++)for(let _=0;_<=1;_++)w+=`
+    `}},cB=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:c,dilationHeight:u,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=fn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let b=0;b<=1;b++)for(let _=0;_<=1;_++)w+=`
           blockIndex = rc.y + ${_};
           pos = rc.x + ${b};
 
           if(blockIndex < ${e[1]} && pos < ${e[0]}) {
             offsetY = int(blockIndex / (${l})) * ${i} - ${p};
-            d0 = offsetY + ${c} * (pos / ${f});
+            d0 = offsetY + ${u} * (pos / ${f});
 
             if(d0 < ${t[y]} && d0 >= 0) {
 
               offsetX = int(mod(float(blockIndex), ${l}.) * ${s}. - ${d}.);
-              d1 = offsetX + ${u} * (int(mod(float(pos), ${f}.) / ${a}.));
+              d1 = offsetX + ${c} * (int(mod(float(pos), ${f}.) / ${a}.));
 
               if(d1 < ${t[g]} && d1 >= 0) {
 
@@ -2154,7 +2154,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         ${m.output} = result;
       }
-    `}};function hb({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=r.texData.get(e.dataId),c=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&c>Q_,w=l[2]%2!=0&&!!u.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=ye({inputs:{x:e},backend:r,attrs:{shape:[1,b,n.inChannels]}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),I=mp({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=ye({inputs:{x:I},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(I)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},x=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(ic(u.shape,_.shape),()=>`packed reshape ${u.shape} to ${_.shape} isn't free`);let I=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(I);let S=mp({a:_,b:I,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),T=r.texData.get(S.dataId);v.assert(T.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=x,T.shape=n.outShape,A=zn({inputs:{x:S},backend:r}),A.shape=n.outShape,y.push(S)}for(let b of y)r.disposeIntermediateTensorInfo(b);return A}function db({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*u*c,A=d*h,y=[m,A],g=!0,w=!1,b=[],_=ye({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(_),b.push(x);let I=new gB(y,_.shape,n),S=r.runWebGLProgram(I,[_],"float32"),T=ye({inputs:{x:S},backend:r,attrs:{shape:[1,y[0],y[1]]}});b.push(S),b.push(T);let M=a!=null,D=s!=null,z=o==="leakyrelu",B=o?pp(o,!0):null,U=new q_(T.shape,x.shape,[1,A,n.outChannels],g,w,M,B,D,z),j=[T,x];if(a&&j.push(a),D&&j.push(s),z){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));j.push(Y),b.push(Y)}let X=r.runWebGLProgram(U,j,"float32"),H=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=ye({inputs:{x:X},backend:r,attrs:{shape:H}});b.push(X);for(let Y of b)r.disposeIntermediateTensorInfo(Y);return ee}function xB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!1,h),p;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))p=hb({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=db({x:a,filter:s,convInfo:d,backend:n});else{let m=new cb(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=ye({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var wB={kernelName:fs,backendName:"webgl",kernelFunc:xB},_B=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
+    `}};function d_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,c=r.texData.get(e.dataId),u=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&u>e_,w=l[2]%2!=0&&!!c.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=ye({inputs:{x:e},backend:r,attrs:{shape:[1,b,n.inChannels]}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=Ap({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=ye({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(N)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},x=c.shape;c.shape=c.shape.slice(),c.shape[c.shape.length-2]++,v.assert(oc(c.shape,_.shape),()=>`packed reshape ${c.shape} to ${_.shape} isn't free`);let N=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let T=Ap({a:_,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),C=r.texData.get(T.dataId);v.assert(C.isPacked,()=>"batchMatMul result is expected to be packed"),c.shape=x,C.shape=n.outShape,A=zn({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let b of y)r.disposeIntermediateTensorInfo(b);return A}function p_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:c,inChannels:u,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*c*u,A=d*h,y=[m,A],g=!0,w=!1,b=[],_=ye({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(_),b.push(x);let N=new cB(y,_.shape,n),T=r.runWebGLProgram(N,[_],"float32"),C=ye({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});b.push(T),b.push(C);let F=a!=null,z=s!=null,B=o==="leakyrelu",V=o?fp(o,!0):null,U=new Xb(C.shape,x.shape,[1,A,n.outChannels],g,w,F,V,z,B),j=[C,x];if(a&&j.push(a),z&&j.push(s),B){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));j.push(Y),b.push(Y)}let X=r.runWebGLProgram(U,j,"float32"),G=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=ye({inputs:{x:X},backend:r,attrs:{shape:G}});b.push(X);for(let Y of b)r.disposeIntermediateTensorInfo(Y);return ee}function hB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!1,h),p;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))p=d_({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=p_({x:a,filter:s,convInfo:d,backend:n});else{let m=new h_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=ye({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var dB={kernelName:fs,backendName:"webgl",kernelFunc:hB},pB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2196,15 +2196,15 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},bB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,u=s?2:3,c=s?3:1;this.userCode=`
+    `}},fB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,c=s?2:3,u=s?3:1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
         ivec4 coords = getOutputCoords();
         int batch = coords[0];
-        int d1 = coords[${c}];
+        int d1 = coords[${u}];
 
-        ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - pads;
+        ivec2 dyCorner = ivec2(coords[${l}], coords[${c}]) - pads;
         int dyRCorner = dyCorner.x;
         int dyCCorner = dyCorner.y;
 
@@ -2249,7 +2249,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},vB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
+    `}},mB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
       void main() {
         ivec5 coords = getOutputCoords();
         int wF = coords.x;
@@ -2291,8 +2291,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},kB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=r-1-e.padInfo.left;this.userCode=`
-      const ivec3 pads = ivec3(${o}, ${l}, ${u});
+    `}},AB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=`
+      const ivec3 pads = ivec3(${o}, ${l}, ${c});
 
       void main() {
         ivec5 coords = getOutputCoords();
@@ -2348,12 +2348,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function NB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,c,i,1,o,u,!1,h),p=new _B(d);return n.runWebGLProgram(p,[a,s],"float32")}var IB={kernelName:Eh,backendName:"webgl",kernelFunc:NB};function SB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(u),d=R.computeConv2DInfo(i,s.shape,o,1,l,c,!1,h),p=new bB(d);return n.runWebGLProgram(p,[a,s],"float32")}var TB={kernelName:ms,backendName:"webgl",kernelFunc:SB};function CB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeConv3DInfo(a.shape,s.shape,i,l,o),c=new yB(u);return n.runWebGLProgram(c,[a,s],"float32")}var EB={kernelName:pu,backendName:"webgl",kernelFunc:CB};function RB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,u=R.computeConv3DInfo(a.shape,l,i,1,o),c=new vB(u);return n.runWebGLProgram(c,[a,s],"float32")}var FB={kernelName:Rh,backendName:"webgl",kernelFunc:RB};function MB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,u=R.computeConv3DInfo(l,s.shape,o,1,i),c=new kB(u);return n.runWebGLProgram(c,[a,s],"float32")}var $B={kernelName:Fh,backendName:"webgl",kernelFunc:MB},DB=G_+`
+    `}};function yB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),p=new pB(d);return n.runWebGLProgram(p,[a,s],"float32")}var gB={kernelName:Rh,backendName:"webgl",kernelFunc:yB};function xB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(c),d=R.computeConv2DInfo(i,s.shape,o,1,l,u,!1,h),p=new fB(d);return n.runWebGLProgram(p,[a,s],"float32")}var wB={kernelName:ms,backendName:"webgl",kernelFunc:xB};function bB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new uB(c);return n.runWebGLProgram(u,[a,s],"float32")}var _B={kernelName:fu,backendName:"webgl",kernelFunc:bB};function vB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,c=R.computeConv3DInfo(a.shape,l,i,1,o),u=new mB(c);return n.runWebGLProgram(u,[a,s],"float32")}var kB={kernelName:Mh,backendName:"webgl",kernelFunc:vB};function IB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,c=R.computeConv3DInfo(l,s.shape,o,1,i),u=new AB(c);return n.runWebGLProgram(u,[a,s],"float32")}var NB={kernelName:Fh,backendName:"webgl",kernelFunc:IB},SB=qb+`
   return cos(x);
-`,OB=Ze({opSnippet:DB}),zB={kernelName:As,backendName:"webgl",kernelFunc:OB},PB=`
+`,TB=Ze({opSnippet:SB}),CB={kernelName:As,backendName:"webgl",kernelFunc:TB},EB=`
   float e2x = exp(-x);
   return (e2x + 1.0 / e2x) / 2.0;
-`,LB=Ze({opSnippet:PB}),WB={kernelName:io,backendName:"webgl",kernelFunc:LB},BB=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[c,h]=n;this.outputShape=[u,c,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=c>1?[`${(i-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,b]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
+`,RB=Ze({opSnippet:EB}),MB={kernelName:io,backendName:"webgl",kernelFunc:RB},FB=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[c]=t,[u,h]=n;this.outputShape=[c,u,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=u>1?[`${(i-1)/(u-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,b]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
       const float height_ratio = float(${m});
       const float width_ratio = float(${g});
       void main() {
@@ -2414,21 +2414,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           setOutput(newValue);
         }
       }
-    `}},VB=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=r,c=new BB(a.shape,s.shape,o,l,u);return n.runWebGLProgram(c,[a,s,i],"float32")},UB={kernelName:oo,backendName:"webgl",kernelFunc:VB},mb=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${pb(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
+    `}},$B=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,u=new FB(a.shape,s.shape,o,l,c);return n.runWebGLProgram(u,[a,s,i],"float32")},DB={kernelName:oo,backendName:"webgl",kernelFunc:$B},A_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${f_(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
       uniform float index;
       void main() {
-        ${ct(r)} coords = getOutputCoords();
-        int end = ${fb(r,"coords")};
+        ${ut(r)} coords = getOutputCoords();
+        int end = ${m_(r,"coords")};
         float val = ${a};
         int pow2 = int(pow(2.0, index));
         if (${i}) {
           int idx = ${o};
-          ${fb(r,"coords")} = idx;
-          val += getX(${pb(r,"coords")});
+          ${m_(r,"coords")} = idx;
+          val += getX(${f_(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 pb(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 ${e} is not yet supported`)}function fb(e,t){if(e===1)return`${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 ${e} is not yet supported`)}function jB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,u=R.getAxesPermutation([s],l),c=a;u!=null&&(c=In({inputs:{x:a},backend:n,attrs:{perm:u}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=c.shape[h],p=zn({inputs:{x:c},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new mb(c.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new mb(c.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(u!=null){let f=R.getUndoAxesPermutation(u),m=In({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(c),m}return p}var HB={kernelName:ys,backendName:"webgl",kernelFunc:jB};function GB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),u=n.readSync(s.dataId),c=R_(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=_P(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var qB={kernelName:Mh,backendName:"webgl",kernelFunc:GB},XB=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function f_(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 ${e} is not yet supported`)}function m_(e,t){if(e===1)return`${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 ${e} is not yet supported`)}function OB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,c=R.getAxesPermutation([s],l),u=a;c!=null&&(u=Nn({inputs:{x:a},backend:n,attrs:{perm:c}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=u.shape[h],p=zn({inputs:{x:u},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new A_(u.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new A_(u.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(c!=null){let f=R.getUndoAxesPermutation(c),m=Nn({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),m}return p}var zB={kernelName:ys,backendName:"webgl",kernelFunc:OB};function PB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),c=n.readSync(s.dataId),u=Mb(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=pP(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var LB={kernelName:$h,backendName:"webgl",kernelFunc:PB},WB=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];
@@ -2447,7 +2447,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
       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 KB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],c=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=u*s,p=c/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new XB(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var ZB={kernelName:lo,backendName:"webgl",kernelFunc:KB},Ab=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
+  `}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 BB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],c=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=c*s,p=u/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new WB(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var VB={kernelName:lo,backendName:"webgl",kernelFunc:BB},y_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?A=`float activation(float a) {
@@ -2460,7 +2460,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         `,y="result = activation(result);");let g=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${A}
 
-      const ivec2 strides = ivec2(${u}, ${c});
+      const ivec2 strides = ivec2(${c}, ${u});
       const ivec2 pads = ivec2(${o}, ${l});
 
       void main() {
@@ -2503,13 +2503,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${y}
         setOutput(result);
       }
-    `}},yb=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`
+    `}},g_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`
           vec4 xTexelR${b}C${_*2} = vec4(0.);
           vec4 wR${b}C${_} = vec4(0.);
           vec4 xR${b}C${_} = vec4(0.);`;for(let b=0;b<p;b++)for(let _=0;_<m;_++){let x=_*2;if(A+=`
           xR = xRCorner + ${b*h};
           xC = xCCorner + ${x*d};
-        `,c===1){if(x<f&&(l%2==1?A+=`
+        `,u===1){if(x<f&&(l%2==1?A+=`
                 xCOffset = xC + 1;
                 if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
                   xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
@@ -2545,8 +2545,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 }
 
                 xR${b}C${x} = xTexelR${b}C${x};
-              `,x+1<f)){let I=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
-                  xCOffset = xC + ${l%2} + ${I};
+              `,x+1<f)){let N=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
+                  xCOffset = xC + ${l%2} + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
@@ -2564,7 +2564,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                   xR${b}C${x+1} = vec4(
                     xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.xy);
                 `):A+=`
-                  xCOffset = xC + ${I};
+                  xCOffset = xC + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
@@ -2575,7 +2575,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 `}}else x<f&&(A+=`
               if(xR >= 0 && xR < ${s}) {
             `,l%2==1?(A+=`
-                xCOffset = xC + 1 - ${c};
+                xCOffset = xC + 1 - ${u};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
                   xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
                 } else {
@@ -2592,7 +2592,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                   xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.zw);
               `,x+1<f&&(A+=`
                   vec4 final = vec4(0.);
-                  xCOffset = xC + 1 + ${c};
+                  xCOffset = xC + 1 + ${u};
                   if(xCOffset >= 0 && xCOffset < ${i}) {
                     final = getX(batch, xR, xCOffset, d1);
                   }
@@ -2604,7 +2604,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                   xTexelR${b}C${x} = vec4(0.);
                 }
 
-                xCOffset = xC + ${c};
+                xCOffset = xC + ${u};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
                   xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
                 } else {
@@ -2633,7 +2633,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }`,g="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${y}
 
-      const ivec2 strides = ivec2(${u}, ${c});
+      const ivec2 strides = ivec2(${c}, ${u});
       const ivec2 pads = ivec2(${o}, ${l});
 
       void main() {
@@ -2656,7 +2656,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${g}
         setOutput(result);
       }
-    `}};function YB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=r,c=l;c==null&&(c=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new yb(h):d=new Ab(h),n.runWebGLProgram(d,[a,s],"float32")}var JB={kernelName:gs,backendName:"webgl",kernelFunc:YB},QB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
+    `}};function UB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:c}=r,u=l;u==null&&(u=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new g_(h):d=new y_(h),n.runWebGLProgram(d,[a,s],"float32")}var jB={kernelName:gs,backendName:"webgl",kernelFunc:UB},HB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2691,7 +2691,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},eV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
+    `}},GB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
       const ivec2 pads = ivec2(${s}, ${i});
 
       void main() {
@@ -2736,15 +2736,15 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function tV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:c}=r,h=R.computeConv2DInfo(a.shape,c,i,o,l,u,!0),d=new QB(h);return n.runWebGLProgram(d,[a,s],"float32")}var nV={kernelName:$h,backendName:"webgl",kernelFunc:tV};function rV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:c}=r,h=R.computeConv2DInfo(c,s.shape,i,o,l,u,!0),d=new eV(h);return n.runWebGLProgram(d,[a,s],"float32")}var aV={kernelName:Dh,backendName:"webgl",kernelFunc:rV},sV=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
+    `}};function qB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r,h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),d=new HB(h);return n.runWebGLProgram(d,[a,s],"float32")}var XB={kernelName:Dh,backendName:"webgl",kernelFunc:qB};function KB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r,h=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),d=new GB(h);return n.runWebGLProgram(d,[a,s],"float32")}var ZB={kernelName:Oh,backendName:"webgl",kernelFunc:KB},YB=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 iV(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=ye({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new sV(s),l=n.runWebGLProgram(o,[i],i.dtype),u=ye({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var oV={kernelName:Oh,backendName:"webgl",kernelFunc:iV},lV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:c,left:h}=r;this.userCode=`
+    `}};function JB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=ye({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new YB(s),l=n.runWebGLProgram(o,[i],i.dtype),c=ye({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),c}var QB={kernelName:zh,backendName:"webgl",kernelFunc:JB},eV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:c}=e,{top:u,left:h}=r;this.userCode=`
       const ivec2 strides = ivec2(${a}, ${s});
-      const ivec2 pads = ivec2(${c}, ${h});
+      const ivec2 pads = ivec2(${u}, ${h});
       const float neg_infinity = -3.4e38;
 
       void main() {
@@ -2762,7 +2762,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
           if (hIn >= 0 && hIn < ${t}) {
             for (int w = 0; w < ${o}; w++) {
-              int wIn = wBeg + w * ${u};
+              int wIn = wBeg + w * ${c};
 
               if (wIn >= 0 && wIn < ${n}) {
                 float xVal = getX(batch, hIn, wIn, d1);
@@ -2780,7 +2780,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         float result = curVal;
         setOutput(result);
       }
-    `}};function uV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),c,h=new lV(u);c=n.runWebGLProgram(h,[a,s],"float32");let d=ye({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var cV={kernelName:fu,backendName:"webgl",kernelFunc:uV},hV="return (x >= 0.0) ? x : (exp(x) - 1.0);",dV=`
+    `}};function tV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,h=new eV(c);u=n.runWebGLProgram(h,[a,s],"float32");let d=ye({inputs:{x:u},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(u),d}var nV={kernelName:mu,backendName:"webgl",kernelFunc:tV},rV="return (x >= 0.0) ? x : (exp(x) - 1.0);",aV=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -2789,12 +2789,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,pV=Ze({opSnippet:hV,packedOpSnippet:dV}),fV={kernelName:uo,backendName:"webgl",kernelFunc:pV},mV="return (b >= 1.0) ? a : a * (b + 1.0);",AV=`
+`,sV=Ze({opSnippet:rV,packedOpSnippet:aV}),iV={kernelName:uo,backendName:"webgl",kernelFunc:sV},oV="return (b >= 1.0) ? a : a * (b + 1.0);",lV=`
   vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
   return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
-`,yV=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hc(AV,r.shape,a.shape):new Fl(mV,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},gV={kernelName:Lh,backendName:"webgl",kernelFunc:yV},xV=`
+`,uV=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new dc(lV,r.shape,a.shape):new Ml(oV,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},cV={kernelName:Wh,backendName:"webgl",kernelFunc:uV},hV=`
   return vec4(equal(a, b));
-`,wV="return float(a == b);",_V=nn({opSnippet:wV,packedOpSnippet:xV,dtype:"bool"}),bV={kernelName:ho,backendName:"webgl",kernelFunc:_V},vV=`
+`,dV="return float(a == b);",pV=nn({opSnippet:dV,packedOpSnippet:hV,dtype:"bool"}),fV={kernelName:ho,backendName:"webgl",kernelFunc:pV},mV=`
   // Error function is calculated approximately with elementary function.
   // See "Handbook of Mathematical Functions with Formulas,
   // Graphs, and Mathematical Tables", Abramowitz and Stegun.
@@ -2809,7 +2809,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
   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));
-`,kV=Ze({opSnippet:vV}),NV={kernelName:co,backendName:"webgl",kernelFunc:kV},gb="return exp(x);",xb=Ze({opSnippet:gb,packedOpSnippet:gb,cpuKernelImpl:kP}),IV={kernelName:ws,backendName:"webgl",kernelFunc:xb};function oA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),ye({inputs:{x:s},backend:r,attrs:{shape:o}})}var SV={kernelName:po,backendName:"webgl",kernelFunc:oA},wb="return exp(x) - 1.0;",TV=Ze({opSnippet:wb,packedOpSnippet:wb,cpuKernelImpl:NP}),CV={kernelName:fo,backendName:"webgl",kernelFunc:TV},_b=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
+`,AV=Ze({opSnippet:mV}),yV={kernelName:co,backendName:"webgl",kernelFunc:AV},x_="return exp(x);",w_=Ze({opSnippet:x_,packedOpSnippet:x_,cpuKernelImpl:AP}),gV={kernelName:ws,backendName:"webgl",kernelFunc:w_};function oA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),ye({inputs:{x:s},backend:r,attrs:{shape:o}})}var xV={kernelName:po,backendName:"webgl",kernelFunc:oA},b_="return exp(x) - 1.0;",wV=Ze({opSnippet:b_,packedOpSnippet:b_,cpuKernelImpl:yP}),bV={kernelName:fo,backendName:"webgl",kernelFunc:wV},__=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
       const float exponentMultiplier = ${a};
 
       float unaryOpComplex(float real, float expR, float imag, float expI) {
@@ -2842,13 +2842,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ivec2 coords = getOutputCoords();
         setOutput(mulMatDFT(coords[0], coords[1]));
       }
-    `}};function bb(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=ye({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,u=new _b("real",l,t),c=new _b("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Ua({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=ye({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function EV(e){let{inputs:t,backend:n}=e,{input:r}=t;return bb(r,!1,n)}var RV={kernelName:Wh,backendName:"webgl",kernelFunc:EV},FV=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
+    `}};function v_(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=ye({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,c=new __("real",l,t),u=new __("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Ua({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=ye({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function _V(e){let{inputs:t,backend:n}=e,{input:r}=t;return v_(r,!1,n)}var vV={kernelName:Bh,backendName:"webgl",kernelFunc:_V},kV=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 lA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new FV(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var MV={kernelName:mu,backendName:"webgl",kernelFunc:lA},$V=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function lA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new kV(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var IV={kernelName:Au,backendName:"webgl",kernelFunc:lA},NV=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];
@@ -2862,7 +2862,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
           setOutput(outputValue);
         }
-    `}},DV={kernelName:mo,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new $V(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},vb="return floor(x);",OV=Ze({opSnippet:vb,packedOpSnippet:vb,cpuKernelImpl:IP}),zV={kernelName:_s,backendName:"webgl",kernelFunc:OV},PV=`
+    `}},SV={kernelName:mo,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new NV(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},k_="return floor(x);",TV=Ze({opSnippet:k_,packedOpSnippet:k_,cpuKernelImpl:gP}),CV={kernelName:bs,backendName:"webgl",kernelFunc:TV},EV=`
   float s = sign(a) * sign(b);
   int ia = round(a);
   int ib = round(b);
@@ -2872,7 +2872,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
   } else {
     return NAN;
   }
-`,LV=`
+`,RV=`
   ivec4 ia = round(a);
   ivec4 ib = round(b);
   bvec4 cond = notEqual(ib, ivec4(0));
@@ -2893,7 +2893,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
     result[3] = idiv(ia[3], ib[3], s[3]);
   }
   return vec4(result);
-`,WV=nn({opSnippet:PV,packedOpSnippet:LV,dtype:"int32"}),BV={kernelName:bs,backendName:"webgl",kernelFunc:WV},VV=class{constructor(e){this.variableNames=["A"];let t=fn(),[n,r]=e;this.outputShape=e,this.userCode=`
+`,MV=nn({opSnippet:EV,packedOpSnippet:RV,dtype:"int32"}),FV={kernelName:_s,backendName:"webgl",kernelFunc:MV},$V=class{constructor(e){this.variableNames=["A"];let t=fn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2915,7 +2915,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         setOutput(floor(value * 255.0 + 0.5));
       }
-    `}},UV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=fn(),[n,r]=e;this.outputShape=e,this.userCode=`
+    `}},DV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=fn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2949,7 +2949,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         ${t.output} = result;
       }
-    `}},HV={kernelName:td,backendName:"webgl",kernelFunc:jV},$l;function jV(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,u]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],c=[u,l],h=[u,l,s];(o||i)&&($l==null&&($l=document.createElement("canvas").getContext("2d")),$l.canvas.width=l,$l.canvas.height=u,$l.drawImage(a,0,0,l,u),a=$l.canvas);let d=n.makeTensorInfo(c,"int32");n.texData.get(d.dataId).usage=Yn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new UV(h):new VV(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function GV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(c),A=R.computeConv2DInfo(a.shape,s.shape,l,h,u,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=hb({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=db({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let b=i!=null,_=o!=null,x=p==="leakyrelu",I=p?pp(p,!1):null,S=new cb(A,b,I,_,x),T=[a,s];if(i&&T.push(i),o&&T.push(o),x){let M=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));T.push(M),g.push(M)}y=n.runWebGLProgram(S,T,"float32")}let w=ye({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var qV={kernelName:ti,backendName:"webgl",kernelFunc:GV};function XV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=c;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,u,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?pp(d,y):null,w=[a,s],b=i!=null,_=o!=null,x=d==="leakyrelu";if(b&&w.push(i),_&&w.push(o),x){let T=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(T),f.push(T)}let I;y?I=new yb(A,b,g,_,x):I=new Ab(A,b,g,_,x);let S=n.runWebGLProgram(I,w,"float32");return f.forEach(T=>n.disposeIntermediateTensorInfo(T)),S}var KV={kernelName:ni,backendName:"webgl",kernelFunc:XV},ZV=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ct(t.length),a=ct(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
+    `}},zV={kernelName:nd,backendName:"webgl",kernelFunc:OV},$l;function OV(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,c]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],u=[c,l],h=[c,l,s];(o||i)&&($l==null&&($l=document.createElement("canvas").getContext("2d")),$l.canvas.width=l,$l.canvas.height=c,$l.drawImage(a,0,0,l,c),a=$l.canvas);let d=n.makeTensorInfo(u,"int32");n.texData.get(d.dataId).usage=Yn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new DV(h):new $V(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function PV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(u),A=R.computeConv2DInfo(a.shape,s.shape,l,h,c,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=d_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=p_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let b=i!=null,_=o!=null,x=p==="leakyrelu",N=p?fp(p,!1):null,T=new h_(A,b,N,_,x),C=[a,s];if(i&&C.push(i),o&&C.push(o),x){let F=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));C.push(F),g.push(F)}y=n.runWebGLProgram(T,C,"float32")}let w=ye({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var LV={kernelName:ti,backendName:"webgl",kernelFunc:PV};function WV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=u;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,c,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?fp(d,y):null,w=[a,s],b=i!=null,_=o!=null,x=d==="leakyrelu";if(b&&w.push(i),_&&w.push(o),x){let C=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(C),f.push(C)}let N;y?N=new g_(A,b,g,_,x):N=new y_(A,b,g,_,x);let T=n.runWebGLProgram(N,w,"float32");return f.forEach(C=>n.disposeIntermediateTensorInfo(C)),T}var BV={kernelName:ni,backendName:"webgl",kernelFunc:WV},VV=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ut(t.length),a=ut(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
         ${r} strides = ${r}(${this.strides});
          void main() {
           ${a} coords = getOutputCoords();
@@ -2960,21 +2960,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
           setOutput(getX(flattenIndex, coords[1]));
         }
-      `}};function YV(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,u,c]=R.prepareAndValidate(r,a),h=ye({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=ye({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/u,u]}}),p=new ZV(i,c,[l,u]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var JV={kernelName:yo,backendName:"webgl",kernelFunc:YV},eU=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ct(this.rank),r=QV(e,2);this.userCode=`
+      `}};function UV(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,c,u]=R.prepareAndValidate(r,a),h=ye({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=ye({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/c,c]}}),p=new VV(i,u,[l,c]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var jV={kernelName:yo,backendName:"webgl",kernelFunc:UV},GV=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ut(this.rank),r=HV(e,2);this.userCode=`
       void main() {
         ${n} resRC = getOutputCoords();
         setOutput(getA(${r}));
       }
-    `}};function QV(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function tU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],u=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),c=v.sizeFromShape(s.shape),h=[],d=ye({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),p=ye({inputs:{x:s},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});h.push(d),h.push(p);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),b=SP(w,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new eU(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=ye({inputs:{x:A},backend:n,attrs:{shape:u.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var nU={kernelName:Ao,backendName:"webgl",kernelFunc:tU},rU="return float(a > b);",aU=`
+    `}};function HV(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function qV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],c=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=v.sizeFromShape(s.shape),h=[],d=ye({inputs:{x:a},backend:n,attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]}}),p=ye({inputs:{x:s},backend:n,attrs:{shape:[c.batchSize,u/c.batchSize]}});h.push(d),h.push(p);let f=[c.batchSize,c.outerSize,u/c.batchSize,c.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),b=xP(w,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(c.outputShape,b.dtype,b.values)}let m=new GV(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=ye({inputs:{x:A},backend:n,attrs:{shape:c.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var XV={kernelName:Ao,backendName:"webgl",kernelFunc:qV},KV="return float(a > b);",ZV=`
   return vec4(greaterThan(a, b));
-`,sU=nn({opSnippet:rU,packedOpSnippet:aU,cpuKernelImpl:TP,dtype:"bool"}),iU={kernelName:go,backendName:"webgl",kernelFunc:sU},oU="return float(a >= b);",lU=`
+`,YV=nn({opSnippet:KV,packedOpSnippet:ZV,cpuKernelImpl:wP,dtype:"bool"}),JV={kernelName:go,backendName:"webgl",kernelFunc:YV},QV="return float(a >= b);",eU=`
   return vec4(greaterThanEqual(a, b));
-`,uU=nn({opSnippet:oU,packedOpSnippet:lU,dtype:"bool"}),cU={kernelName:ks,backendName:"webgl",kernelFunc:uU};function hU(e){let{inputs:t,backend:n}=e,{input:r}=t;return bb(r,!0,n)}var dU={kernelName:Bh,backendName:"webgl",kernelFunc:hU},pU="return float(!isnan(x) && !isinf(x));",fU=Ze({opSnippet:pU,dtype:"bool"}),mU={kernelName:xo,backendName:"webgl",kernelFunc:fU},AU="return float(isinf(x));",yU=Ze({opSnippet:AU,dtype:"bool"}),gU={kernelName:wo,backendName:"webgl",kernelFunc:yU},xU="return float(isnan(x));",wU=Ze({opSnippet:xU,dtype:"bool"}),_U={kernelName:_o,backendName:"webgl",kernelFunc:wU},bU="return float(a < b);",vU=`
+`,tU=nn({opSnippet:QV,packedOpSnippet:eU,dtype:"bool"}),nU={kernelName:ks,backendName:"webgl",kernelFunc:tU};function rU(e){let{inputs:t,backend:n}=e,{input:r}=t;return v_(r,!0,n)}var aU={kernelName:Vh,backendName:"webgl",kernelFunc:rU},sU="return float(!isnan(x) && !isinf(x));",iU=Ze({opSnippet:sU,dtype:"bool"}),oU={kernelName:xo,backendName:"webgl",kernelFunc:iU},lU="return float(isinf(x));",uU=Ze({opSnippet:lU,dtype:"bool"}),cU={kernelName:wo,backendName:"webgl",kernelFunc:uU},hU="return float(isnan(x));",dU=Ze({opSnippet:hU,dtype:"bool"}),pU={kernelName:bo,backendName:"webgl",kernelFunc:dU},fU="return float(a < b);",mU=`
   return vec4(lessThan(a, b));
-`,kU=nn({opSnippet:bU,packedOpSnippet:vU,cpuKernelImpl:CP,dtype:"bool"}),NU={kernelName:bo,backendName:"webgl",kernelFunc:kU},IU="return float(a <= b);",SU=`
+`,AU=nn({opSnippet:fU,packedOpSnippet:mU,cpuKernelImpl:bP,dtype:"bool"}),yU={kernelName:_o,backendName:"webgl",kernelFunc:AU},gU="return float(a <= b);",xU=`
   return vec4(lessThanEqual(a, b));
-`,TU=nn({opSnippet:IU,packedOpSnippet:SU,dtype:"bool"}),CU={kernelName:vo,backendName:"webgl",kernelFunc:TU};function EU(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=EP(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var RU={kernelName:Uh,backendName:"webgl",kernelFunc:EU},FU=`if (x < 0.0) return NAN;
-  return log(x);`,MU=`
+`,wU=nn({opSnippet:gU,packedOpSnippet:xU,dtype:"bool"}),bU={kernelName:vo,backendName:"webgl",kernelFunc:wU};function _U(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=_P(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var vU={kernelName:jh,backendName:"webgl",kernelFunc:_U},kU=`if (x < 0.0) return NAN;
+  return log(x);`,IU=`
   vec4 result = log(x);
   vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
   result.r = isNaN.r == 1.0 ? NAN : result.r;
@@ -2983,16 +2983,16 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
   result.a = isNaN.a == 1.0 ? NAN : result.a;
 
   return result;
-`,$U=Ze({opSnippet:FU,packedOpSnippet:MU,cpuKernelImpl:RP}),DU={kernelName:Ss,backendName:"webgl",kernelFunc:$U},OU="return log(1.0 + x);",zU=Ze({opSnippet:OU}),PU={kernelName:ko,backendName:"webgl",kernelFunc:zU},LU="return float(a >= 1.0 && b >= 1.0);",WU=`
+`,NU=Ze({opSnippet:kU,packedOpSnippet:IU,cpuKernelImpl:vP}),SU={kernelName:Ss,backendName:"webgl",kernelFunc:NU},TU="return log(1.0 + x);",CU=Ze({opSnippet:TU}),EU={kernelName:ko,backendName:"webgl",kernelFunc:CU},RU="return float(a >= 1.0 && b >= 1.0);",MU=`
   return vec4(
     vec4(greaterThanEqual(a, vec4(1.0))) *
     vec4(greaterThanEqual(b, vec4(1.0))));
-`,BU=nn({opSnippet:LU,packedOpSnippet:WU,dtype:"bool"}),VU={kernelName:No,backendName:"webgl",kernelFunc:BU},UU="return float(!(x >= 1.0));",jU=Ze({opSnippet:UU}),HU={kernelName:Au,backendName:"webgl",kernelFunc:jU},GU="return float(a >= 1.0 || b >= 1.0);",qU=`
+`,FU=nn({opSnippet:RU,packedOpSnippet:MU,dtype:"bool"}),$U={kernelName:Io,backendName:"webgl",kernelFunc:FU},DU="return float(!(x >= 1.0));",OU=Ze({opSnippet:DU}),zU={kernelName:yu,backendName:"webgl",kernelFunc:OU},PU="return float(a >= 1.0 || b >= 1.0);",LU=`
   return min(
     vec4(greaterThanEqual(a, vec4(1.0))) +
     vec4(greaterThanEqual(b, vec4(1.0))),
     vec4(1.0));
-`,XU=nn({opSnippet:GU,packedOpSnippet:qU,dtype:"bool"}),KU={kernelName:yu,backendName:"webgl",kernelFunc:XU},ZU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+`,WU=nn({opSnippet:PU,packedOpSnippet:LU,dtype:"bool"}),BU={kernelName:gu,backendName:"webgl",kernelFunc:WU},VU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3011,7 +3011,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         float val = x * ${o};
         setOutput(val);
       }
-    `}},YU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+    `}},UU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords.x;
@@ -3073,7 +3073,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         vec4 result = xAtOutputCoords * ${o};
         setOutput(result);
       }
-    `}},JU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,u=J().getBool("WEBGL_PACK_NORMALIZATION")?new YU(a.shape,s,i,o,l):new ZU(a.shape,s,i,o,l);return n.runWebGLProgram(u,[a],a.dtype)},QU={kernelName:gu,backendName:"webgl",kernelFunc:JU},ej=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
+    `}},jU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,c=J().getBool("WEBGL_PACK_NORMALIZATION")?new UU(a.shape,s,i,o,l):new VU(a.shape,s,i,o,l);return n.runWebGLProgram(c,[a],a.dtype)},HU={kernelName:xu,backendName:"webgl",kernelFunc:jU},GU=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3128,14 +3128,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
       }
       setOutput(result);
       }
-    `}},tj=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:c}=r,h=new ej(a.shape,o,l,u,c);return n.runWebGLProgram(h,[a,s,i],a.dtype)},nj={kernelName:jh,backendName:"webgl",kernelFunc:tj};function rj(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,e.dtype,"max",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function kb(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let x=0;x<w.length;x++)w[x]=a.shape[c[x]];let b=tA(g,a.shape,a.dtype,c,w);p=n.makeTensorInfo(w,a.dtype);let _=n.texData.get(p.dataId);_.values=b}else p=fp(a,c,n);u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("max",u,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,u),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=FP(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let b=n.texData.get(y.dataId);b.values=w}else y=rj(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var aj={kernelName:Ts,backendName:"webgl",kernelFunc:kb},sj=B_+`
+    `}},qU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:c,beta:u}=r,h=new GU(a.shape,o,l,c,u);return n.runWebGLProgram(h,[a,s,i],a.dtype)},XU={kernelName:Hh,backendName:"webgl",kernelFunc:qU};function KU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,e.dtype,"max",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function I_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let x=0;x<w.length;x++)w[x]=a.shape[u[x]];let b=tA(g,a.shape,a.dtype,u,w);p=n.makeTensorInfo(w,a.dtype);let _=n.texData.get(p.dataId);_.values=b}else p=mp(a,u,n);c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("max",c,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,c),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=kP(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let b=n.texData.get(y.dataId);b.values=w}else y=KU(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var ZU={kernelName:Ts,backendName:"webgl",kernelFunc:I_},YU=Vb+`
   return max(a, b);
-`,ij=`
+`,JU=`
   vec4 result = vec4(max(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+dp+`
+  `+pp+`
   return result;
-`,oj=nn({opSnippet:sj,packedOpSnippet:ij,cpuKernelImpl:MP}),lj={kernelName:Cs,backendName:"webgl",kernelFunc:oj};function uj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return zn({inputs:{x:a},backend:n});let h=new dc(c,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var cj={kernelName:Es,backendName:"webgl",kernelFunc:uj};function hj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,u,l),d=new aA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var dj={kernelName:xu,backendName:"webgl",kernelFunc:hj},pj=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
+`,QU=nn({opSnippet:YU,packedOpSnippet:JU,cpuKernelImpl:IP}),ej={kernelName:Cs,backendName:"webgl",kernelFunc:QU};function tj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return zn({inputs:{x:a},backend:n});let h=new pc(u,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var nj={kernelName:Es,backendName:"webgl",kernelFunc:tj};function rj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,c,l),d=new aA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var aj={kernelName:wu,backendName:"webgl",kernelFunc:rj},sj=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
@@ -3181,8 +3181,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},fj=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=u-1-e.padInfo.left,p=o*l*u-1;this.userCode=`
-      const ivec3 pads = ivec3(${c}, ${h}, ${d});
+    `}},ij=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,c=e.effectiveFilterWidth,u=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=c-1-e.padInfo.left,p=o*l*c-1;this.userCode=`
+      const ivec3 pads = ivec3(${u}, ${h}, ${d});
 
       void main() {
         ivec5 coords = getOutputCoords();
@@ -3218,7 +3218,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             }
             int idyR = int(dyR);
 
-            for (int wC = 0; wC < ${u};
+            for (int wC = 0; wC < ${c};
                 wC += ${i}) {
               float dyC = float(dyCCorner + wC) / ${r}.0;
 
@@ -3235,8 +3235,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
               // Get the current value, check it against the value from the
               // position matrix.
               int curPosValue =
-                  wD * ${l} * ${u} +
-                  wR * ${u} + wC;
+                  wD * ${l} * ${c} +
+                  wR * ${c} + wC;
               float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
 
               dotProd += dyValue * mask;
@@ -3245,14 +3245,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function mj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new aA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new fj(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var Aj={kernelName:Gh,backendName:"webgl",kernelFunc:mj};function yj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;kl([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,u,1,c,h),p=!0,f=new dc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new pj(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var gj={kernelName:Hh,backendName:"webgl",kernelFunc:yj};function xj(e,t,n,r){let a=new dc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new dc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var wj={kernelName:qh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=R.computePool2DInfo(r.shape,a,s,u,i),[h,d]=xj(r,o,c,l);return[h,d]}};function _j(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,"float32","mean",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var bj={kernelName:Rs,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,b=new Array(o);for(let I=0;I<b.length;I++)b[I]=r.shape[c[I]];let _=tA(w,r.shape,r.dtype,c,b);f=i.makeTensorInfo(b,r.dtype);let x=i.texData.get(f.dataId);x.values=_}else f=fp(r,c,i);p.push(f),u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("sum",u,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,u),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=_j(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function vj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var kj={kernelName:Fs,backendName:"webgl",kernelFunc:vj},Nj=B_+`
+    `}};function oj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new aA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new ij(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var lj={kernelName:qh,backendName:"webgl",kernelFunc:oj};function uj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;kl([s,i],"maxPoolGrad");let{filterSize:l,strides:c,pad:u,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,c,1,u,h),p=!0,f=new pc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new sj(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var cj={kernelName:Gh,backendName:"webgl",kernelFunc:uj};function hj(e,t,n,r){let a=new pc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new pc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var dj={kernelName:Xh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let c=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${c}'`);let u=R.computePool2DInfo(r.shape,a,s,c,i),[h,d]=hj(r,o,u,l);return[h,d]}};function pj(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,"float32","mean",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var fj={kernelName:Rs,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,b=new Array(o);for(let N=0;N<b.length;N++)b[N]=r.shape[u[N]];let _=tA(w,r.shape,r.dtype,u,b);f=i.makeTensorInfo(b,r.dtype);let x=i.texData.get(f.dataId);x.values=_}else f=mp(r,u,i);p.push(f),c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("sum",c,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,c),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=pj(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function mj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=Nn({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var Aj={kernelName:Ms,backendName:"webgl",kernelFunc:mj},yj=Vb+`
   return min(a, b);
-`,Ij=`
+`,gj=`
   vec4 result = vec4(min(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+dp+`
+  `+pp+`
   return result;
-`,Sj=nn({opSnippet:Nj,packedOpSnippet:Ij,cpuKernelImpl:$P}),Tj={kernelName:Ms,backendName:"webgl",kernelFunc:Sj},Cj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let r=e.length,a=ct(r),s=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
+`,xj=nn({opSnippet:yj,packedOpSnippet:gj,cpuKernelImpl:NP}),wj={kernelName:Fs,backendName:"webgl",kernelFunc:xj},bj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((c,u)=>c[0]+e[u]+c[1]);let r=e.length,a=ut(r),s=t.map(c=>c[0]).join(","),i=t.map((c,u)=>c[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
 
@@ -3281,7 +3281,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${a} coords = outC - start;
         setOutput(getX(${o}));
       }
-    `}},Ej=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=ct(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=mn("rc",r),l=mn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
+    `}},_j=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=ut(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=mn("rc",r),l=mn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
         ${a} source = rc;
         if (source < start) {
           source = start * 2 - source - ${h};
@@ -3292,11 +3292,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
       `;d=`
         ${a} rc = outputLoc;
         ${p}
-        result[0] = getChannel(getX(${l.join()}), ${c});
+        result[0] = getChannel(getX(${l.join()}), ${u});
         ${o[r-1]} += 1;
-        if(${u}) {
+        if(${c}) {
           ${p}
-          result[1] = getChannel(getX(${l.join()}), ${c});
+          result[1] = getChannel(getX(${l.join()}), ${u});
         }
       `}else{let p=`
         ${a} source = rc;
@@ -3310,21 +3310,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
       `;d=`
         ${a} rc = outputLoc;
         ${p}
-        result[0] = getChannel(getX(${l.join()}), ${c});
+        result[0] = getChannel(getX(${l.join()}), ${u});
         ${o[r-1]} += 1;
-        if(${u}) {
+        if(${c}) {
           ${p}
-          result[1] = getChannel(getX(${l.join()}), ${c});
+          result[1] = getChannel(getX(${l.join()}), ${u});
         }
         rc = outputLoc;
         ${o[r-2]} += 1;
         if(${o[r-2]} < ${this.outputShape[r-2]}) {
           ${p}
-          result[2] = getChannel(getX(${l.join()}), ${c});
+          result[2] = getChannel(getX(${l.join()}), ${u});
           ${o[r-1]} += 1;
-          if(${u}) {
+          if(${c}) {
             ${p}
-            result[3] = getChannel(getX(${l.join()}), ${c});
+            result[3] = getChannel(getX(${l.join()}), ${u});
           }
         }
       `}this.userCode=`
@@ -3337,13 +3337,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${d}
         setOutput(result);
       }
-    `}},Rj=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Ej(r.shape,a,s):new Cj(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},Fj={kernelName:wu,backendName:"webgl",kernelFunc:Rj},Mj=`if (b == 0.0) return NAN;
-  return mod(a, b);`,$j=`
+    `}},vj=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new _j(r.shape,a,s):new bj(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},kj={kernelName:bu,backendName:"webgl",kernelFunc:vj},Ij=`if (b == 0.0) return NAN;
+  return mod(a, b);`,Nj=`
   vec4 result = mod(a, b);
   vec4 isNaN = vec4(equal(b, vec4(0.0)));
-  `+dp+`
+  `+pp+`
   return result;
-`,Dj=nn({opSnippet:Mj,packedOpSnippet:$j}),Oj={kernelName:Io,backendName:"webgl",kernelFunc:Dj},zj=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
+`,Sj=nn({opSnippet:Ij,packedOpSnippet:Nj}),Tj={kernelName:No,backendName:"webgl",kernelFunc:Sj},Cj=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
       uniform float seed;
 
       void main() {
@@ -3365,11 +3365,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         // 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)}}},Pj=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},Ej=`
 if (a == b) {
   return 1.0;
 };
-return a / b;`,Lj=`
+return a / b;`,Rj=`
   // vec4 one = vec4(equal(a, b));
   // return one + (vec4(1.0) - one) * a / b;
   vec4 result = a / b;
@@ -3387,14 +3387,14 @@ return a / b;`,Lj=`
   }
 
   return result;
-`,Nb=nn({opSnippet:Pj,packedOpSnippet:Lj,checkOutOfBounds:!0}),Wj={kernelName:xs,backendName:"webgl",kernelFunc:Nb},Ib="return a - b;",Sb=nn({opSnippet:Ib,packedOpSnippet:Ib,supportsComplex:!0,cpuKernelImpl:VP}),Bj={kernelName:Ys,backendName:"webgl",kernelFunc:Sb};function Tb(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=kb({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),u=ye({inputs:{x:o},backend:n,attrs:{shape:l}}),c=Sb({inputs:{a,b:u},backend:n}),h=xb({inputs:{x:c},backend:n}),d=rA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=ye({inputs:{x:d},backend:n,attrs:{shape:l}}),f=Nb({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var Vj={kernelName:Ks,backendName:"webgl",kernelFunc:Tb};function Uj(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:Tb({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),u=l.shape[0],c=l.shape[1],h=new zj(u,c,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var jj={kernelName:Xh,backendName:"webgl",kernelFunc:Uj},Cb="return -x;";function Hj(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=OP(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new El(r.shape,Cb):a=new Va(r.shape,Cb),n.runWebGLProgram(a,[r],r.dtype)}var Gj={kernelName:So,backendName:"webgl",kernelFunc:Hj},qj=Wr.nonMaxSuppressionV3Impl;function Xj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,u=n.readSync(a.dataId),c=n.readSync(s.dataId),{selectedIndices:h}=qj(u,c,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var Kj={kernelName:Co,backendName:"webgl",kernelFunc:Xj},Zj=Wr.nonMaxSuppressionV4Impl;function Yj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=Zj(c,h,i,o,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var Jj={kernelName:Eo,backendName:"webgl",kernelFunc:Yj},Qj=Wr.nonMaxSuppressionV5Impl;function eH(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=u,{selectedIndices:A,selectedScores:y}=Qj(c,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var tH={kernelName:Ro,backendName:"webgl",kernelFunc:eH},nH=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
+`,N_=nn({opSnippet:Ej,packedOpSnippet:Rj,checkOutOfBounds:!0}),Mj={kernelName:xs,backendName:"webgl",kernelFunc:N_},S_="return a - b;",T_=nn({opSnippet:S_,packedOpSnippet:S_,supportsComplex:!0,cpuKernelImpl:$P}),Fj={kernelName:Ys,backendName:"webgl",kernelFunc:T_};function C_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=I_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),c=ye({inputs:{x:o},backend:n,attrs:{shape:l}}),u=T_({inputs:{a,b:c},backend:n}),h=w_({inputs:{x:u},backend:n}),d=rA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=ye({inputs:{x:d},backend:n,attrs:{shape:l}}),f=N_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var $j={kernelName:Ks,backendName:"webgl",kernelFunc:C_};function Dj(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:C_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=l.shape[0],u=l.shape[1],h=new Cj(c,u,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var Oj={kernelName:Kh,backendName:"webgl",kernelFunc:Dj},E_="return -x;";function zj(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=TP(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new El(r.shape,E_):a=new Va(r.shape,E_),n.runWebGLProgram(a,[r],r.dtype)}var Pj={kernelName:So,backendName:"webgl",kernelFunc:zj},Lj=Wr.nonMaxSuppressionV3Impl;function Wj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,c=n.readSync(a.dataId),u=n.readSync(s.dataId),{selectedIndices:h}=Lj(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var Bj={kernelName:Co,backendName:"webgl",kernelFunc:Wj},Vj=Wr.nonMaxSuppressionV4Impl;function Uj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=Vj(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var jj={kernelName:Eo,backendName:"webgl",kernelFunc:Uj},Hj=Wr.nonMaxSuppressionV5Impl;function Gj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=Hj(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var qj={kernelName:Ro,backendName:"webgl",kernelFunc:Gj},Xj=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)));
       }
-    `}},rH=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),u=new nH(l,s,i,o),c=ye({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(u,[c],a.dtype);n.disposeIntermediateTensorInfo(c);let d=[...a.shape,s],p=ye({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},aH={kernelName:Ds,backendName:"webgl",kernelFunc:rH};function xp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=fc({inputs:{input:r},backend:n}),s=xp({inputs:{x:a},backend:n}),i=gp({inputs:{input:r},backend:n}),o=xp({inputs:{x:i},backend:n}),l=Ua({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return lA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var sH={kernelName:Ko,backendName:"webgl",kernelFunc:xp};function Eb(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=fc({inputs:{input:r},backend:n}),s=Eb({inputs:{x:a},backend:n}),i=gp({inputs:{input:r},backend:n}),o=xp({inputs:{x:i},backend:n}),l=Ua({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return lA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var iH={kernelName:Fo,backendName:"webgl",kernelFunc:Eb};function oH(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return oA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(c=>{let h=oA({inputs:{input:c},backend:n,attrs:{dim:a}});return o.push(h),h}),u=ub({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var lH={kernelName:Mo,backendName:"webgl",kernelFunc:oH},uH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let r=e.length,a=ct(r),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
+    `}},Kj=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),c=new Xj(l,s,i,o),u=ye({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(c,[u],a.dtype);n.disposeIntermediateTensorInfo(u);let d=[...a.shape,s],p=ye({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},Zj={kernelName:Ds,backendName:"webgl",kernelFunc:Kj};function wp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=mc({inputs:{input:r},backend:n}),s=wp({inputs:{x:a},backend:n}),i=xp({inputs:{input:r},backend:n}),o=wp({inputs:{x:i},backend:n}),l=Ua({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return lA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var Yj={kernelName:Ko,backendName:"webgl",kernelFunc:wp};function R_(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=mc({inputs:{input:r},backend:n}),s=R_({inputs:{x:a},backend:n}),i=xp({inputs:{input:r},backend:n}),o=wp({inputs:{x:i},backend:n}),l=Ua({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return lA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var Jj={kernelName:Mo,backendName:"webgl",kernelFunc:R_};function Qj(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return oA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{v.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let h=oA({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=c_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var eH={kernelName:Fo,backendName:"webgl",kernelFunc:Qj},tH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,c)=>l[0]+e[c]+l[1]);let r=e.length,a=ut(r),s=t.map(l=>l[0]).join(","),i=t.map((l,c)=>l[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
         uniform float value;
@@ -3421,19 +3421,19 @@ return a / b;`,Lj=`
           setOutput(getX(${o}));
         }
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},cH=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=ct(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=mn("rc",r),l=mn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
-       if(${u}) {
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},nH=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=ut(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=mn("rc",r),l=mn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
+       if(${c}) {
       `,r===1?"":`}
        rc = outputLoc;
        ${o[r-2]} += 1;
        if(${o[r-2]} < ${this.outputShape[r-2]}) {`,r===1?"":`  ${o[r-1]} += 1;
-         if(${u}) {`],d=r===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let f=0,m=r===1?2:4;f<m;f++)p+=`
+         if(${c}) {`],d=r===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let f=0,m=r===1?2:4;f<m;f++)p+=`
         ${h[f]}
         if (${d}) {
           result[${f}] = float(value);
         } else {
           ${a} source = rc - start;
-          result[${f}] = getChannel(getX(${l.join()}), ${c});
+          result[${f}] = getChannel(getX(${l.join()}), ${u});
         }
       `;p+=r===1?"} ":"}}",this.userCode=`
       const ${a} start = ${a}(${s});
@@ -3446,7 +3446,7 @@ return a / b;`,Lj=`
         ${p}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},Rb=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new cH(a.shape,s,i):new uH(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},hH={kernelName:Os,backendName:"webgl",kernelFunc:Rb},dH=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},M_=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new nH(a.shape,s,i):new tH(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},rH={kernelName:Os,backendName:"webgl",kernelFunc:M_},aH=`
   if(a < 0.0 && floor(b) < b){
     return NAN;
   }
@@ -3455,7 +3455,7 @@ return a / b;`,Lj=`
   }
   return (round(mod(b, 2.0)) != 1) ?
       pow(abs(a), b) : sign(a) * pow(abs(a), b);
-`,pH=`
+`,sH=`
   // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
   vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
   vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
@@ -3469,11 +3469,11 @@ return a / b;`,Lj=`
   result.a = isExpZero.a ? 1.0 : result.a;
 
   vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
-  `+dp+`
+  `+pp+`
   return result;
-`,fH=nn({opSnippet:dH,packedOpSnippet:pH}),mH={kernelName:zs,backendName:"webgl",kernelFunc:fH};function AH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],u=v.parseAxisParam(s,a.shape),c=u,h=R.getAxesPermutation(c,o),d=a;h!=null&&(d=In({inputs:{x:a},backend:n,attrs:{perm:h}}),c=R.getInnerMostAxes(c.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",c,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=zP(d.shape,d.dtype,f,c);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,c),A=v.sizeFromShape(m),y=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=id(a.dtype),w=vi(y,g,"prod",n);p=ye({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,u);p=ye({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var yH={kernelName:$o,backendName:"webgl",kernelFunc:AH},Fb=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=PP(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},gH={kernelName:_u,backendName:"webgl",kernelFunc:Fb},xH="return 1.0 / x;",wH=Ze({opSnippet:xH}),_H={kernelName:Do,backendName:"webgl",kernelFunc:wH},bH=wr+`
+`,iH=nn({opSnippet:aH,packedOpSnippet:sH}),oH={kernelName:zs,backendName:"webgl",kernelFunc:iH};function lH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],c=v.parseAxisParam(s,a.shape),u=c,h=R.getAxesPermutation(u,o),d=a;h!=null&&(d=Nn({inputs:{x:a},backend:n,attrs:{perm:h}}),u=R.getInnerMostAxes(u.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",u,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=CP(d.shape,d.dtype,f,u);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,u),A=v.sizeFromShape(m),y=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=od(a.dtype),w=vi(y,g,"prod",n);p=ye({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,c);p=ye({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var uH={kernelName:$o,backendName:"webgl",kernelFunc:lH},F_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=EP(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},cH={kernelName:_u,backendName:"webgl",kernelFunc:F_},hH="return 1.0 / x;",dH=Ze({opSnippet:hH}),pH={kernelName:Do,backendName:"webgl",kernelFunc:dH},fH=wr+`
   return (x < 0.0) ? 0.0 : x;
-`,vH=`
+`,mH=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3483,9 +3483,9 @@ return a / b;`,Lj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,kH=Ze({opSnippet:bH,packedOpSnippet:vH}),NH={kernelName:Ls,backendName:"webgl",kernelFunc:kH},IH=wr+`
+`,AH=Ze({opSnippet:fH,packedOpSnippet:mH}),yH={kernelName:Ls,backendName:"webgl",kernelFunc:AH},gH=wr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,SH=`
+`,xH=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3495,10 +3495,10 @@ return a / b;`,Lj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,TH=Ze({opSnippet:IH,packedOpSnippet:SH}),CH={kernelName:Bs,backendName:"webgl",kernelFunc:TH},EH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+`,wH=Ze({opSnippet:gH,packedOpSnippet:xH}),bH={kernelName:Bs,backendName:"webgl",kernelFunc:wH},_H=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
-          ${u[0]/c[0]},
-          ${u[1]/c[1]});
+          ${c[0]/u[0]},
+          ${c[1]/u[1]});
       const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
 
       void main() {
@@ -3528,11 +3528,11 @@ return a / b;`,Lj=`
 
         setOutput(newValue);
       }
-    `}},RH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}},vH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec3 effectiveInputOverOutputRatioRC = vec3(
-          ${u[0]/c[0]},
-          ${u[1]/c[1]},
-          ${u[1]/c[1]});
+          ${c[0]/u[0]},
+          ${c[1]/u[1]},
+          ${c[1]/u[1]});
       const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
                                      ${o}.0);
 
@@ -3605,7 +3605,7 @@ return a / b;`,Lj=`
 
         setOutput(newValue);
       }
-    `}};function FH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new RH(a.shape,l,u,s,i):new EH(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],"float32")}var MH={kernelName:Ws,backendName:"webgl",kernelFunc:FH},$H=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function kH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new vH(a.shape,l,c,s,i):new _H(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],"float32")}var IH={kernelName:Ws,backendName:"webgl",kernelFunc:kH},NH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3615,8 +3615,8 @@ return a / b;`,Lj=`
 
         float accumulator = 0.0;
 
-        const float heightScale = float(${u});
-        const float widthScale = float(${c});
+        const float heightScale = float(${c});
+        const float widthScale = float(${u});
 
         const float invHeightScale = float(${h});
         const float invWidthScale = float(${d});
@@ -3686,10 +3686,10 @@ return a / b;`,Lj=`
 
         setOutput(accumulator);
       }
-    `}};function DH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new $H(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var OH={kernelName:Yh,backendName:"webgl",kernelFunc:DH},zH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};function SH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new NH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var TH={kernelName:Jh,backendName:"webgl",kernelFunc:SH},CH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
-          ${u[0]/c[0]},
-          ${u[1]/c[1]});
+          ${c[0]/u[0]},
+          ${c[1]/u[1]});
       const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
 
       void main() {
@@ -3708,7 +3708,7 @@ return a / b;`,Lj=`
 
         setOutput(newValue);
       }
-    `}};function PH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=new zH(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],a.dtype)}var LH={kernelName:bu,backendName:"webgl",kernelFunc:PH},WH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function EH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=new CH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],a.dtype)}var RH={kernelName:vu,backendName:"webgl",kernelFunc:EH},MH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3718,8 +3718,8 @@ return a / b;`,Lj=`
 
         float accumulator = 0.0;
 
-        const float heightScale = float(${u});
-        const float widthScale = float(${c});
+        const float heightScale = float(${c});
+        const float widthScale = float(${u});
 
         const float invHeightScale = float(${h});
         const float invWidthScale = float(${d});
@@ -3778,17 +3778,17 @@ return a / b;`,Lj=`
 
         setOutput(accumulator);
       }
-    `}};function BH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new WH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var VH={kernelName:Zh,backendName:"webgl",kernelFunc:BH},UH=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=`
+    `}};function FH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new MH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var $H={kernelName:Yh,backendName:"webgl",kernelFunc:FH},DH=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
         void main() {
           int coord = getOutputCoords();
           setOutput(getX(${e[0]} - coord - 1));
         }
-      `;return}let r=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>r(o)).join(","),s=ct(n);this.userCode=`
+      `;return}let r=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>r(o)).join(","),s=ut(n);this.userCode=`
       void main() {
         ${s} coords = getOutputCoords();
         setOutput(getX(${a}));
       }
-    `}},jH=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-${n} tensor is not yet supported`);this.outputShape=e;let r=mn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ct(n);n===1?this.userCode=`
+    `}},OH=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=mn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ut(n);n===1?this.userCode=`
         void main(){
           int rc = getOutputCoords();
           vec4 result = vec4(0.);
@@ -3809,14 +3809,14 @@ return a / b;`,Lj=`
             result.g = ${l(r.slice())};
           }
           if(${s}) {
-            result.b = ${u(r.slice())};
+            result.b = ${c(r.slice())};
             if(${a}) {
-              result.a = ${c(r.slice())};
+              result.a = ${u(r.slice())};
             }
           }
           setOutput(result);
         }
-    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function u(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function c(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function HH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return zn({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new jH(a.shape,o):new UH(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var GH={kernelName:Vs,backendName:"webgl",kernelFunc:HH},qH=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
+    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function c(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function u(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function zH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return zn({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new OH(a.shape,o):new DH(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var PH={kernelName:Vs,backendName:"webgl",kernelFunc:zH},LH=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
         vec3 fill = vec3(${t.join(",")});
         float outputValue = fill[coords[3]];`,this.userCode=`
         uniform vec4 params;
@@ -3836,7 +3836,7 @@ return a / b;`,Lj=`
           }
           setOutput(outputValue);
         }
-    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},XH={kernelName:Zo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new qH(r.shape,s),[u,c]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(u,c,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},KH=`
+    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},WH={kernelName:Zo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new LH(r.shape,s),[c,u]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(c,u,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},BH=`
   // OpenGL ES does not support round function.
   // The algorithm is based on banker's rounding.
   float base = floor(x);
@@ -3851,7 +3851,7 @@ return a / b;`,Lj=`
       return base + 1.0;
     }
   }
-`,ZH=Ze({opSnippet:KH}),YH={kernelName:Us,backendName:"webgl",kernelFunc:ZH},JH="return inversesqrt(x);",QH=Ze({opSnippet:JH,cpuKernelImpl:LP}),eG={kernelName:js,backendName:"webgl",kernelFunc:QH},Mb=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ct(a.length),l=ct(s.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
+`,VH=Ze({opSnippet:BH}),UH={kernelName:Us,backendName:"webgl",kernelFunc:VH},jH="return inversesqrt(x);",HH=Ze({opSnippet:jH,cpuKernelImpl:RP}),GH={kernelName:js,backendName:"webgl",kernelFunc:HH},$_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ut(a.length),l=ut(s.length),c="";n===1?c="i":n===2&&(c="i, j");let u=`getIndices(${c})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
         ${o} strides = ${o}(${a});
 
         void main() {
@@ -3861,7 +3861,7 @@ return a / b;`,Lj=`
           for (int i = 0; i < ${e}; i++) {
             int flattenedIndex = 0;
             for (int j = 0; j < ${t}; j++) {
-              int index = round(${c});
+              int index = round(${u});
               flattenedIndex += index * ${p};
             }
             if (flattenedIndex == coords[0]) {
@@ -3871,7 +3871,7 @@ return a / b;`,Lj=`
           }
           setOutput(mix(getDefaultValue(), sum, float(found)));
         }
-      `}};function tG(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:u,strides:c,outputSize:h}=R.calculateShapes(s,a,i),d=[h/u,u];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=ye({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=ye({inputs:{x:s},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new Mb(l,o,p.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=ye({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var nG={kernelName:zo,backendName:"webgl",kernelFunc:tG},rG=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);r=o.join(),a=l.join()}let s=ct(n);this.userCode=`
+      `}};function qH(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:c,strides:u,outputSize:h}=R.calculateShapes(s,a,i),d=[h/c,c];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=ye({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=ye({inputs:{x:s},backend:n,attrs:{shape:[l,c]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new $_(l,o,p.shape.length,f.shape.length,u,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=ye({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var XH={kernelName:zo,backendName:"webgl",kernelFunc:qH},KH=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let c=0;c<t.length;c++)l.push(`${i[c]}`),c<e&&o.push(`${i[c]}`);r=o.join(),a=l.join()}let s=ut(n);this.userCode=`
       void main() {
         ${s} resRC = getOutputCoords();
         float cVal = getC(${r});
@@ -3881,21 +3881,21 @@ return a / b;`,Lj=`
           setOutput(getB(${a}));
         }
       }
-    `}};function aG(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new rG(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],ar(a.dtype,s.dtype))}var sG={kernelName:Po,backendName:"webgl",kernelFunc:aG},iG=`
+    `}};function ZH(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new KH(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],ar(a.dtype,s.dtype))}var YH={kernelName:Po,backendName:"webgl",kernelFunc:ZH},JH=`
   // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
   // see: https://arxiv.org/abs/1706.02515
   float scaleAlpha = ${R.SELU_SCALEALPHA};
   float scale = ${R.SELU_SCALE};
   return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
-`,oG=Ze({opSnippet:iG}),lG={kernelName:Lo,backendName:"webgl",kernelFunc:oG},uG="return 1.0 / (1.0 + exp(-1.0 * x));",cG=Ze({opSnippet:uG}),hG={kernelName:Gs,backendName:"webgl",kernelFunc:cG},dG=`
+`,QH=Ze({opSnippet:JH}),eG={kernelName:Lo,backendName:"webgl",kernelFunc:QH},tG="return 1.0 / (1.0 + exp(-1.0 * x));",nG=Ze({opSnippet:tG}),rG={kernelName:Gs,backendName:"webgl",kernelFunc:nG},aG=`
   if (isnan(x)) { return 0.0; }
   return sign(x);
-`,pG=Ze({opSnippet:dG}),fG={kernelName:Vo,backendName:"webgl",kernelFunc:pG},mG=G_+`
+`,sG=Ze({opSnippet:aG}),iG={kernelName:Vo,backendName:"webgl",kernelFunc:sG},oG=qb+`
   return sin(x);
-`,AG=Ze({opSnippet:mG}),yG={kernelName:Hs,backendName:"webgl",kernelFunc:AG},gG=`
+`,lG=Ze({opSnippet:oG}),uG={kernelName:Hs,backendName:"webgl",kernelFunc:lG},cG=`
   float e2x = exp(x);
   return (e2x - 1.0 / e2x) / 2.0;
-`,xG=Ze({opSnippet:gG}),wG={kernelName:Bo,backendName:"webgl",kernelFunc:xG},_G=`
+`,hG=Ze({opSnippet:cG}),dG={kernelName:Bo,backendName:"webgl",kernelFunc:hG},pG=`
   float epsilon = 1.1920928955078125e-7;
   float threshold = log(epsilon) + 2.0;
 
@@ -3915,9 +3915,9 @@ return a / b;`,Lj=`
     result = log(exp_x + 1.0);
   }
   return result;
-`,bG=Ze({opSnippet:_G}),vG={kernelName:Uo,backendName:"webgl",kernelFunc:bG},kG=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let u=[],c=Rb({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(c.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(c.shape,s,o,!1),f=ye({inputs:{x:c},backend:n,attrs:{shape:h}}),m=In({inputs:{x:f},backend:n,attrs:{perm:d}}),A=ye({inputs:{x:m},backend:n,attrs:{shape:p}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},NG={kernelName:vu,backendName:"webgl",kernelFunc:kG};function IG(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:u,strides:c,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new Mb(u,l,a.shape.length,s.shape.length,c,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var SG={kernelName:Jh,backendName:"webgl",kernelFunc:IG};function TG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),u=a.shape.length,c=new Array(u).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=pc({inputs:{x:a},backend:n,attrs:{begin:c,size:p}});return c[o]+=d,f})}var CG={kernelName:jo,backendName:"webgl",kernelFunc:TG},EG="return sqrt(x);",RG=Ze({opSnippet:EG}),FG={kernelName:qs,backendName:"webgl",kernelFunc:RG},MG="return x * x;",$G=Ze({opSnippet:MG}),DG={kernelName:ku,backendName:"webgl",kernelFunc:$G},$b="return (a - b) * (a - b);",OG=nn({opSnippet:$b,packedOpSnippet:$b}),zG={kernelName:Zs,backendName:"webgl",kernelFunc:OG};function PG({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=wr+`
+`,fG=Ze({opSnippet:pG}),mG={kernelName:Uo,backendName:"webgl",kernelFunc:fG},AG=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let c=[],u=M_({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(u.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(u.shape,s,o,!1),f=ye({inputs:{x:u},backend:n,attrs:{shape:h}}),m=Nn({inputs:{x:f},backend:n,attrs:{perm:d}}),A=ye({inputs:{x:m},backend:n,attrs:{shape:p}});return c.push(u),c.push(f),c.push(m),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},yG={kernelName:ku,backendName:"webgl",kernelFunc:AG};function gG(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:c,strides:u,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new $_(c,l,a.shape.length,s.shape.length,u,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var xG={kernelName:Qh,backendName:"webgl",kernelFunc:gG};function wG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),c=a.shape.length,u=new Array(c).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=fc({inputs:{x:a},backend:n,attrs:{begin:u,size:p}});return u[o]+=d,f})}var bG={kernelName:jo,backendName:"webgl",kernelFunc:wG},_G="return sqrt(x);",vG=Ze({opSnippet:_G}),kG={kernelName:qs,backendName:"webgl",kernelFunc:vG},IG="return x * x;",NG=Ze({opSnippet:IG}),SG={kernelName:Iu,backendName:"webgl",kernelFunc:NG},D_="return (a - b) * (a - b);",TG=nn({opSnippet:D_,packedOpSnippet:D_}),CG={kernelName:Zs,backendName:"webgl",kernelFunc:TG};function EG({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=wr+`
     return x > 0.0 ? 1.0 : float(${t.alpha});
-  `,s=new Va(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var LG={kernelName:Ca,backendName:"webgl",kernelFunc:PG},WG=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ct(n.length),s=ct(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,u)=>(o++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
+  `,s=new Va(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var RG={kernelName:Ca,backendName:"webgl",kernelFunc:EG},MG=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ut(n.length),s=ut(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,c)=>(o++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${o-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
       ${a} begin = ${a}(${e});
       ${a} strides = ${a}(${t});
 
@@ -3925,15 +3925,15 @@ return a / b;`,Lj=`
         ${s} coords = getOutputCoords();
         setOutput(getX(${i}));
       }
-    `}};function BG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=cn.sliceInfo(a.shape,s,i,o,l,u,c,h,d),w=ye({inputs:{x:a},backend:n,attrs:{shape:y}}),b;if(p){let x=pc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});b=ye({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))b=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let x=n.texData.get(w.dataId).values,I=We(w.shape,w.dtype,x),S=BP(g,I,m,f);b=n.makeTensorInfo(g,w.dtype,S.values)}else{let x=new WG(f,m,g);b=n.runWebGLProgram(x,[w],w.dtype)}let _=ye({inputs:{x:b},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(b),_}var VG={kernelName:Ho,backendName:"webgl",kernelFunc:BG},UG="return tan(x);",jG=Ze({opSnippet:UG}),HG={kernelName:Go,backendName:"webgl",kernelFunc:jG},GG=`
+    `}};function FG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=cn.sliceInfo(a.shape,s,i,o,l,c,u,h,d),w=ye({inputs:{x:a},backend:n,attrs:{shape:y}}),b;if(p){let x=fc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});b=ye({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))b=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let x=n.texData.get(w.dataId).values,N=We(w.shape,w.dtype,x),T=FP(g,N,m,f);b=n.makeTensorInfo(g,w.dtype,T.values)}else{let x=new MG(f,m,g);b=n.runWebGLProgram(x,[w],w.dtype)}let _=ye({inputs:{x:b},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(b),_}var $G={kernelName:Ho,backendName:"webgl",kernelFunc:FG},DG="return tan(x);",OG=Ze({opSnippet:DG}),zG={kernelName:Go,backendName:"webgl",kernelFunc:OG},PG=`
   float e2x = exp(-2.0 * abs(x));
   return sign(x) * (1.0 - e2x) / (1.0 + e2x);
-`,qG=Ze({opSnippet:GG}),XG={kernelName:Js,backendName:"webgl",kernelFunc:qG},ZG=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=ct(this.rank),a=KG(e);this.userCode=`
+`,LG=Ze({opSnippet:PG}),WG={kernelName:Js,backendName:"webgl",kernelFunc:LG},VG=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=ut(this.rank),a=BG(e);this.userCode=`
       void main() {
         ${r} resRC = getOutputCoords();
         setOutput(getA(${a}));
       }
-    `}};function KG(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function Db(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(c=>v.decodeString(c)),l=We(a.shape,a.dtype,o),u=UP(l,s);return n.makeTensorInfo(u.shape,u.dtype,u.values)}let i=new ZG(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var YG={kernelName:Ta,backendName:"webgl",kernelFunc:Db};function JG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,u]=jP(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var QG={kernelName:qo,backendName:"webgl",kernelFunc:JG},eq=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
+    `}};function BG(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function O_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(u=>v.decodeString(u)),l=We(a.shape,a.dtype,o),c=DP(l,s);return n.makeTensorInfo(c.shape,c.dtype,c.values)}let i=new VG(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var UG={kernelName:Ta,backendName:"webgl",kernelFunc:O_};function jG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,c]=OP(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(c.shape,c.dtype,c.values)]}var HG={kernelName:qo,backendName:"webgl",kernelFunc:jG},GG=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
             float mapCoord(float outCoord, float len) {
               float inCoord = outCoord;
               if(${o} == 2) {
@@ -4045,7 +4045,7 @@ return a / b;`,Lj=`
               }
               setOutput(outputValue);
             }
-        `}};function tq(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=r,[c,h,d,p]=a.shape,[f,m]=u!=null?u:[h,d],A=[c,f,m,p],y=new eq(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var nq={kernelName:Qh,backendName:"webgl",kernelFunc:tq};function rq(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;kl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=HP(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([u.length],"int32",u)]}var aq={kernelName:ed,backendName:"webgl",kernelFunc:rq};function sq(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],u=new Array(o-1),c=0;for(let m=0;m<o;m++)m!==s&&(u[c++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=pc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=ye({inputs:{x:A},backend:n,attrs:{shape:u}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var iq={kernelName:Xo,backendName:"webgl",kernelFunc:sq},oq=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,h=`
+        `}};function qG(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:c}=r,[u,h,d,p]=a.shape,[f,m]=c!=null?c:[h,d],A=[u,f,m,p],y=new GG(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var XG={kernelName:ed,backendName:"webgl",kernelFunc:qG};function KG(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;kl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:c}=zP(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([c.length],"int32",c)]}var ZG={kernelName:td,backendName:"webgl",kernelFunc:KG};function YG(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],c=new Array(o-1),u=0;for(let m=0;m<o;m++)m!==s&&(c[u++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=fc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=ye({inputs:{x:A},backend:n,attrs:{shape:c}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var JG={kernelName:Xo,backendName:"webgl",kernelFunc:YG},QG=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",c=Math.floor(n/4)*4,u=n%4,h=`
         sumValue += dot(values, segFilter);
     `,d="";a%n>0&&(d=`
         if (inIdx < 0 || inIdx >= ${a}) {
@@ -4078,7 +4078,7 @@ return a / b;`,Lj=`
 
         float sumValue = 0.0;
 
-        for (int i = 0; i < ${u}; i += 4) {
+        for (int i = 0; i < ${c}; i += 4) {
           int inIdx = inOffset + i;
           vec4 values = vec4(
             getValue(batch, inIdx),
@@ -4097,8 +4097,8 @@ return a / b;`,Lj=`
           ${h}
         }
 
-        int inIdx = inOffset + ${u};
-        if (${c===1}) {
+        int inIdx = inOffset + ${c};
+        if (${u===1}) {
           vec4 values = vec4(
             getValue(batch, inIdx),
             initializationValue,
@@ -4116,7 +4116,7 @@ return a / b;`,Lj=`
           );
 
           ${h}
-        } else if (${c===2}) {
+        } else if (${u===2}) {
           vec4 values = vec4(
             getValue(batch, inIdx),
             getValue(batch, inIdx + 1),
@@ -4132,7 +4132,7 @@ return a / b;`,Lj=`
           );
 
           ${h}
-        } else if (${c===3}) {
+        } else if (${u===3}) {
           vec4 values = vec4(
             getValue(batch, inIdx),
             getValue(batch, inIdx + 1),
@@ -4151,26 +4151,26 @@ return a / b;`,Lj=`
         }
         setOutput(${l});
       }
-    `}};function lq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r,o=a.shape.length,l=[],u=0,c=R.getAxesPermutation([u],o),h=a;c!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:c}}),l.push(h),u=R.getInnerMostAxes(1,o)[0]);let d=R.segment_util.computeOutShape(h.shape,u,i),p=v.sizeFromShape([h.shape[u]]),f=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=id(a.dtype),A=(b,_,x,I,S)=>{let T=b.shape[0],M=b.shape[1],D=R.segment_util.segOpComputeOptimalWindowSize(M,S),z={windowSize:D,inSize:M,batchSize:T,numSegments:S},B=new oq(z,_),U=n.compileAndRun(B,[b,x],I);if(l.push(U),U.shape[1]===S)return U;let j=Fb({backend:n,attrs:{start:0,stop:S,step:1,dtype:"float32"}}),X=Db({inputs:{x:j},backend:n,attrs:{reps:[M/D]}});return l.push(j),l.push(X),A(U,_,X,I,S)},y=A(f,"unsortedSegmentSum",s,m,i),g=ye({inputs:{x:y},backend:n,attrs:{shape:d}}),w=g;if(c!=null){l.push(g);let b=R.getUndoAxesPermutation(c);w=In({inputs:{x:w},backend:n,attrs:{perm:b}})}return l.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var uq={kernelName:Nu,backendName:"webgl",kernelFunc:lq},cq=[QU,nj,BL,UL,GL,KL,YL,eW,nW,aW,lW,cW,pW,AW,vW,xW,IW,EW,TW,$W,OW,PW,VW,KW,YW,rB,sB,uB,dB,bL,AB,IB,TB,wB,FB,$B,EB,zB,WB,UB,HB,qB,ZB,nV,aV,JB,oV,cV,fV,gV,bV,NV,IV,SV,CV,RV,MV,DV,zV,BV,HV,qV,KV,JV,nU,iU,cU,_L,dU,mB,mU,gU,_U,kL,NU,CU,RU,PU,DU,VU,HU,KU,aj,dj,cj,Aj,gj,wj,lj,bj,kj,Tj,Fj,Oj,jj,CL,Gj,Kj,Jj,tH,QW,aH,iH,lH,hH,mH,IL,yH,gH,eB,Wj,_H,CH,NH,RL,MH,OH,LH,VH,GH,XH,YH,eG,nG,sG,lG,hG,fG,yG,wG,qW,Vj,vG,NG,SG,CG,FG,DG,zG,LG,VG,Bj,PL,HG,XG,YG,QG,nq,LL,aq,iq,uq,sH];for(let e of cq)ri(e);var Pn;(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"})(Pn||(Pn={}));var mc;(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"})(mc||(mc={}));var Ob;function hq(e){Ob=e.wasm.cwrap(ei,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function dq(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t;if(a.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:h}=r,d=n.dataIdMap.get(a.dataId).id,p=n.dataIdMap.get(s.dataId).id,f=0;if(i!=null){let S=n.dataIdMap.get(i.dataId);if(S.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${S.shape.length}.`);f=S.id}let m=o==null?0:n.dataIdMap.get(o.dataId).id,A=mc[c];if(A==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?a.shape[2]:a.shape[1],g=u?s.shape[1]:s.shape[2],w=a.shape[0],b=n.makeOutput([w,y,g],a.dtype),_=n.dataIdMap.get(b.dataId).id,x=new Uint8Array(new Int32Array(a.shape).buffer),I=new Uint8Array(new Int32Array(s.shape).buffer);return Ob(d,x,a.shape.length,p,I,s.shape.length,l,u,A,f,m,h||0,_),b}var pq={kernelName:ei,backendName:"wasm",setupFunc:hq,kernelFunc:dq};function Sn(e){let t;function n(a){t=a.wasm.cwrap(e,null,["number","number"])}function r(a){let{backend:s,inputs:{x:i}}=a,o=s.dataIdMap.get(i.dataId).id,l=s.makeOutput(i.shape,i.dtype),u=s.dataIdMap.get(l.dataId).id;return v.sizeFromShape(l.shape)===0||t(o,u),l}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var fq=Sn(Yi);function An(e,t,n){let r;function a(i){r=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:c}=l,h=o.dataIdMap.get(u.dataId).id,d=o.dataIdMap.get(c.dataId).id,p=n!=null?n:u.dtype,f=R.assertAndGetBroadcastShape(u.shape,c.shape),m=o.makeOutput(f,p);if(v.sizeFromShape(f)===0)return m;let A=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(c.shape).buffer),g=o.dataIdMap.get(m.dataId).id,w=()=>r(h,A,u.shape.length,d,y,c.shape.length,Pn[u.dtype],g);if(t&&u.dtype==="float32")return w(),m;let b=R.getBroadcastDims(u.shape,f),_=R.getBroadcastDims(c.shape,f),x=b.every((S,T)=>S===T),I=_.every((S,T)=>S===T);if(x&&I)return w(),m;throw new Error(`Broadcasting along outer dims is not yet supported for ${u.dtype} ${e}.`)}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:s}}var mq=!0,Aq=An(Ia,mq),zb;function yq(e){zb=e.wasm.cwrap(ls,null,["array","number","number","number"])}function gq(e){let{inputs:t,backend:n}=e,r=n.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(r.shape)===0)return r;let a=t.map(o=>n.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(a).buffer),i=n.dataIdMap.get(r.dataId).id;return zb(s,a.length,Pn[r.dtype],i),r}var xq={kernelName:ls,backendName:"wasm",setupFunc:yq,kernelFunc:gq};function wp(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype),a=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(r).set(a),r}var wq={kernelName:Ns,backendName:"wasm",kernelFunc:wp},Pb;function _q(e){Pb=e.wasm.cwrap(Qs,null,["number","array","number","number","number","array","number"])}function _p(e){let{inputs:t,backend:n,attrs:r}=e,[a,s]=vq(t.x.shape,r.perm),i=!0;for(let f=0;f<s.length;f++)s[f]!==f&&(i=!1);let o=bq(t.x.shape,r.perm),l={dataId:t.x.dataId,shape:a,dtype:t.x.dtype};if(i){let f=wp({inputs:t,backend:n});return f.shape=o,f}let u=n.makeOutput(o,l.dtype),c=n.dataIdMap.get(l.dataId).id,h=n.dataIdMap.get(u.dataId).id,d=new Uint8Array(new Int32Array(s).buffer),p=new Uint8Array(new Int32Array(l.shape).buffer);return Pb(c,p,l.shape.length,Pn[l.dtype],h,d,s.length),u}function bq(e,t){let n=new Array(e.length);for(let r=0;r<n.length;r++)n[r]=e[t[r]];return n}function vq(e,t){let n=[],r=[];for(let a=0;a<e.length;++a)e[a]!==1&&n.push(e[a]),e[t[a]]!==1&&r.push(t[a]);for(let a=0;a<r.length;++a){let s=-1;for(let i=0;i<r.length;++i)r[i]>=a&&(s===-1||r[s]>r[i])&&(s=i);r[s]=a}return[n,r]}var kq={kernelName:Qs,backendName:"wasm",kernelFunc:_p,setupFunc:_q};function Dl(e,t,n){let r=e.shape,a=e.shape.length,s=v.parseAxisParam(t,r),i=s,o=R.getAxesPermutation(i,a),l=null,u=!1;if(o!=null){let c=new Array(a);for(let d=0;d<c.length;d++)c[d]=r[o[d]];i=R.getInnerMostAxes(i.length,a),l=_p({inputs:{x:e},attrs:{perm:o},backend:n});let h=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==h&&(u=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:u}}var Lb;function Nq(e){Lb=e.wasm.cwrap(us,null,["number","number","number","number","number"])}function Iq(e){let{backend:t,inputs:n,attrs:r}=e,{axis:a}=r,{x:s}=n,i=t.dataIdMap.get(s.dataId).id,o=i,l=s,{transposed:u,axes:c,inputWasTransposed:h}=Dl(s,a,t);if(h){let y=t.dataIdMap.get(u.dataId).id;y!==i&&(l=u,o=y)}let d=l.shape.slice(0,-1),p=t.makeOutput(d,"int32"),f=t.dataIdMap.get(p.dataId).id,m=v.sizeFromShape(p.shape),A=l.shape[c[0]];return Lb(o,Pn[l.dtype],m,A,f),h&&t.disposeData(u.dataId),p}var Sq={kernelName:us,backendName:"wasm",kernelFunc:Iq,setupFunc:Nq},Wb;function Tq(e){Wb=e.wasm.cwrap(cs,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Cq(e){let{inputs:t,attrs:n,backend:r}=e,a=t.x,s=r.dataIdMap.get(a.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,c=R.computePool2DInfo(a.shape,i,o,1,l,u),h=c.filterHeight,d=c.filterWidth,p=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,A=c.padInfo.left,y=c.strideHeight,g=c.strideWidth,w=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"),_=r.dataIdMap.get(b.dataId).id;return Wb(s,a.shape[0],a.shape[1],a.shape[2],h,d,p,f,m,A,y,g,w,_),b}var Eq={kernelName:cs,backendName:"wasm",setupFunc:Tq,kernelFunc:Cq};function _r(e){let{inputs:t,attrs:n}=e,{x:r}=t,{shape:a}=n,s=v.sizeFromShape(r.shape),i=v.inferFromImplicitShape(a,s);return v.assert(s===v.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${r.shape}. 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Provided ${n} not understood: ${JSON.stringify(e)}`)}function R7(e,t){return Wte(e,t,"classWeight")}async function F7(e,t,n,r){if(t!=null||r!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let a=W(()=>{if(e.shape.length===1)return e.clone();if(e.shape.length===2)if(e.shape[1]>1){let o=1;return e.argMax(o)}else{if(e.shape[1]===1)return e.reshape([e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await a.data());Te(a);let i=[];return s.forEach(o=>{if(n[o]==null)throw new Error(`classWeight must contain all classes in the training data. 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Use LayersModel.compile(modelCompileConfig)."),v.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),v.assert(n.epochs!=null&&n.epochs>0&&Number.isInteger(n.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`),v.assert(!r||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),v.assert(n.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. 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t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),s=[],i=()=>{let u=[];for(let p=0;p<this.inputs.length;++p)u.push({key:this.inputs[p],value:n[p]});let c=new Ei(u),h=Cc(this.outputs,c,{training:!0}),d;for(let p=0;p<this.lossFunctions.length;++p){let f=this.lossFunctions[p](r[p],h[p]);a[p]!=null&&(f=Bte(f,a[p]));let m=kt(f);t.push(m),p===0?d=f:d=se(d,f)}for(let p=0;p<this.metricsTensors.length;++p){let f;if(this.outputs.length>1&&p<this.outputs.length)f=t[p];else{let m=this.metricsTensors[p][0],A=this.metricsTensors[p][1];f=kt(m(r[A],h[A]))}Gt(f),s.push(f)}return d=kt(d),this.calculateLosses().forEach(p=>{d=se(d,p)}),d},o=this.collectedTrainableWeights.map(u=>u.read()),l=!0;return[this.optimizer_.minimize(i,l,o)].concat(s)}}makeTestFunction(){this.testFunction=e=>W(()=>{let 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e.metrics)a[s]=Ni(e.metrics[s])}this.compile({loss:r,metrics:a,optimizer:n})}async save(e,t){if(typeof e=="string"){let i=bn.getSaveHandlers(e);if(i.length===0)throw new V(`Cannot find any save handlers for URL '${e}'`);if(i.length>1)throw new V(`Found more than one (${i.length}) save handlers for URL '${e}'`);e=i[0]}if(e.save==null)throw new V("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await bn.encodeWeights(this.getNamedWeights(t)),r=!1,a=null,s={modelTopology:this.toJSON(a,r),format:ene,generatedBy:`TensorFlow.js tfjs-layers v${qA}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){s.trainingConfig=this.getTrainingConfig();let i="optimizer",{data:o,specs:l}=await bn.encodeWeights(await this.optimizer.getWeights(),i);n.specs.push(...l),n.data=bn.concatenateArrayBuffers([n.data,o])}if(this.userDefinedMetadata!=null){let 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};iy.className="ThresholdedReLU";re.registerClass(iy);var oy=class extends Ke{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new QA().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};oy.className="Softmax";re.registerClass(oy);function Vl(e,t,n){if(typeof e=="number")return ki(e,t);if(e.length!==t)throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let r=0;r<t;++r){let a=e[r];if(!OQ(a))throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${a}`)}return e}function Sr(e,t,n,r,a=1){if(e==null)return e;let s=t+(t-1)*(a-1),i;return n==="same"?i=e:i=e-s+1,Math.floor((i+r-1)/r)}function Xp(e,t,n,r){if(e==null)return null;if(r==="valid")e=e*t+Ga([n-t,0]);else if(r==="same")e=e*t;else throw new V(`Unsupport padding mode: ${r}.`);return e}function ly(e,t){return W(()=>(Ct(t),t==="channelsFirst"?at(e,[0,2,3,1]):e))}function nv(e,t){return W(()=>(Ct(t),t==="channelsFirst"?at(e,[0,2,3,4,1]):e))}function hne(e,t,n,r=1,a="valid",s,i=1){return W(()=>{if(s==null&&(s=br()),Ct(s),e.shape.length!==3)throw new V(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new V(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new V(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=at(e,[0,2,1])),a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=md(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Hr(o,n)),o})}function rv(e,t,n,r=[1,1],a="valid",s,i,o=null){return W(()=>{if(s==null&&(s=br()),Ct(s),e.rank!==3&&e.rank!==4)throw new V(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new V(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=ly(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Wa.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=at(l,[0,3,1,2])),l})}function dne(e,t,n,r=[1,1,1],a="valid",s,i){return W(()=>{if(s==null&&(s=br()),Ct(s),e.rank!==4&&e.rank!==5)throw new V(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new V(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=nv(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=Yf(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Hr(o,n)),s==="channelsFirst"&&(o=at(o,[0,4,1,2,3])),o})}var uy=class extends Ke{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",uy.verifyArgs(t),this.rank=e,Xt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new De(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Vl(t.kernelSize,e,"kernelSize"),this.strides=Vl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Jn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Ct(this.dataFormat),this.activation=Ka(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=xt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Ut(t.biasConstraint),this.biasRegularizer=wt(t.biasRegularizer),this.activityRegularizer=wt(t.activityRegularizer),this.dilationRate=Vl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new V(`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 V(`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 V(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Ur("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!yA(e.kernelSize,"number",1,3))throw new V(`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:Nt(this.biasInitializer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),biasConstraint:Vt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Fc=class extends uy{constructor(e,t){super(e,t);this.kernel=null,Fc.verifyArgs(t),this.filters=t.filters,Xt(this.filters,"filters"),this.kernelInitializer=xt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Ut(t.kernelConstraint),this.kernelRegularizer=wt(t.kernelRegularizer)}build(e){e=ht(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V(`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 W(()=>{e=Pe(e);let n,r=this.bias==null?null:this.bias.read(),a=V3(this.activation.getClassName());if(a!=null&&this.rank===2)n=rv(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,a);else{if(this.rank===1)n=hne(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=rv(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=dne(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new De("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=ht(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let a=0;a<n.length;++a){let s=Sr(n[a],this.kernelSize[a],this.padding,this.strides[a],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[a]);t.push(s)}let r=[e[0]];return this.dataFormat==="channelsLast"?(r=r.concat(t),r.push(this.filters)):(r.push(this.filters),r=r.concat(t)),r}getConfig(){let e={filters:this.filters,kernelInitializer:Nt(this.kernelInitializer),kernelRegularizer:dt(this.kernelRegularizer),kernelConstraint:Vt(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 V(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Mc=class extends Fc{constructor(e){super(2,e);Mc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!yA(e.kernelSize,"number",1,2))throw new V(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Mc.className="Conv2D";re.registerClass(Mc);var Kp=class extends Fc{constructor(e){super(3,e);Kp.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 V(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Kp.className="Conv3D";re.registerClass(Kp);var cy=class extends Mc{constructor(e){super(e);if(this.inputSpec=[new Kt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=ht(e),e.length!==4)throw new V("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Kt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return W(()=>{let n=Pe(e);if(n.shape.length!==4)throw new V(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],u=this.kernelSize[0],c=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=Xp(o,h,u,this.padding),f=Xp(l,d,c,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=at(n,[0,2,3,1]));let A=Ad(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=at(A,[0,3,1,2])),this.bias!=null&&(A=Hr(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=ht(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=Xp(t[r],o,s,this.padding),t[a]=Xp(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};cy.className="Conv2DTranspose";re.registerClass(cy);var av=class extends Fc{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 V("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new V("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 V(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=xt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=wt(t.depthwiseRegularizer),this.depthwiseConstraint=Ut(t.depthwiseConstraint),this.pointwiseInitializer=xt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=wt(t.pointwiseRegularizer),this.pointwiseConstraint=Ut(t.pointwiseConstraint)}build(e){if(e=ht(e),e.length<this.rank+2)throw new V(`Inputs to SeparableConv${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 V(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Kt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return W(()=>{e=Pe(e);let n;if(this.rank===1)throw new De("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=at(e,[0,2,3,1])),n=mm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=at(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Nt(this.depthwiseInitializer),e.pointwiseInitializer=Nt(this.pointwiseInitializer),e.depthwiseRegularizer=dt(this.depthwiseRegularizer),e.pointwiseRegularizer=dt(this.pointwiseRegularizer),e.depthwiseConstraint=Vt(this.depthwiseConstraint),e.pointwiseConstraint=Vt(this.pointwiseConstraint),e}};av.className="SeparableConv";var hy=class extends av{constructor(e){super(2,e)}};hy.className="SeparableConv2D";re.registerClass(hy);var Zp=class extends Fc{constructor(e){super(1,e);Zp.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"&&!yA(e.kernelSize,"number",1,1))throw new V(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Zp.className="Conv1D";re.registerClass(Zp);var dy=class extends Ke{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 W(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=Ip(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Ip(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Ip(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Ip(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}};dy.className="Cropping2D";re.registerClass(dy);var py=class extends Ke{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,Ct(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,MQ(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 W(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=at(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return at(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};py.className="UpSampling2D";re.registerClass(py);function pne(e,t,n=[1,1],r="valid",a,s){return W(()=>{a==null&&(a=br()),Ct(a);let i=ly(e,a);if(e.rank!==4)throw new V(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new V(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=cl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=at(i,[0,3,1,2])),i})}var fy=class extends uy{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=xt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Ut(e.depthwiseConstraint),this.depthwiseRegularizer=wt(e.depthwiseRegularizer)}build(e){if(e=ht(e),e.length<4)throw new V(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${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 W(()=>{e=Pe(e);let n=pne(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=ht(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Sr(t,this.kernelSize[0],this.padding,this.strides[0]),s=Sr(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Nt(this.depthwiseInitializer),e.depthwiseRegularizer=dt(this.depthwiseRegularizer),e.depthwiseConstraint=Vt(this.depthwiseRegularizer),e}};fy.className="DepthwiseConv2D";re.registerClass(fy);function sv(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new V("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function iv(e,t,n,r=!1,a,s,i=!1,o=!1){return W(()=>{let l=t.shape.length;if(l<3)throw new V(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(kr(2,l));if(t=at(t,u),s!=null)throw new De("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=hn(a,-1)),a=at(a,u)),r&&(t=Dn(t,0),a!=null&&(a=Dn(a,0)));let c=[],h,d=n,p=t.shape[0],f=or(t),m;a!=null&&(m=or(a));for(let y=0;y<p;++y){let g=f[y],w=W(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let b=W(()=>{let _=m[y],x=$n(_).sub(_),I=w[0].mul(_).add(d[0].mul(x)),S=d.map((T,M)=>w[1][M].mul(_).add(T.mul(x)));return{output:I,newStates:S}});h=b.output,d=b.newStates}o&&c.push(h)}let A;return o&&(A=dn(c,1)),[h,A,d]})}var Gr=class extends Ke{constructor(e){super(e);let t;if(e.cell==null)throw new V("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Yp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new V("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 Kt({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 kr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){zA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return W(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new De("Constants support is not implemented in RNN yet.");zA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Kt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new De("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new V(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Kt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){W(()=>{if(!this.stateful)throw new ca("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new V("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=>Ft([n,r])):this.states_=[Ft([n,this.cell.stateSize])];else if(e==null)Te(this.states_),this.keptStates!=null&&(Te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Ft([n,r])):this.states_[0]=Ft([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):Te(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new V(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Gt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=sv(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Kt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof Nr){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let c=super.apply(o,t);return this.inputSpec=u,c}else return super.apply(e,t)}call(e,t){return W(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new V(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=iv((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],c=o[2];this.stateful&&this.resetStates(c,r);let h=this.returnSequences?u:l;return this.returnState?[h].concat(c):h})}getInitialState(e){return W(()=>{let t=Ft(e.shape);return t=Ce(t,[1,2]),t=vc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?vA(t,[1,n]):t):this.cell.stateSize>1?[vA(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()===Gr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=Ir(r,n);return new e(Object.assign(t,{cell:a}))}};Gr.className="RNN";re.registerClass(Gr);var Ic=class extends Ke{},Jp=class extends Ic{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=xt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=wt(e.kernelRegularizer),this.recurrentRegularizer=wt(e.recurrentRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ht(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 W(()=>{if(e=e,e.length!==2)throw new V(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=jr(P(e,s),this.kernel.read()):a=jr(e,this.kernel.read()),this.bias!=null&&(a=Hr(a,this.bias.read())),i!=null&&(n=P(n,i));let o=se(a,jr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Xa(this.activation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};Jp.className="SimpleRNNCell";re.registerClass(Jp);var my=class extends Gr{constructor(e){e.cell=new Jp(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};my.className="SimpleRNN";re.registerClass(my);var Qp=class extends Ic{constructor(e){super(e);if(this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new V("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ka(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=xt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=wt(e.kernelRegularizer),this.recurrentRegularizer=wt(e.recurrentRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ht(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 W(()=>{if(e=e,e.length!==2)throw new V(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let u=jr(e,this.kernel.read());this.useBias&&(u=Hr(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,s[0]));let c=this.recurrentKernel.read(),[h,d]=Wt(c,[2*this.units,this.units],c.rank-1),p=jr(r,h),[f,m,A]=Wt(u,3,u.rank-1),[y,g]=Wt(p,2,p.rank-1);i=this.recurrentActivation.apply(se(f,y)),o=this.recurrentActivation.apply(se(m,g));let w=jr(P(o,r),d);l=this.activation.apply(se(A,w));let b=se(P(i,r),P(se(1,vt(i)),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:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};Qp.className="GRUCell";re.registerClass(Qp);var Ay=class extends Gr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Qp(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ay.className="GRU";re.registerClass(Ay);var $c=class extends Ic{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ka(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=xt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=wt(e.kernelRegularizer),this.recurrentRegularizer=wt(e.recurrentRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=ht(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends cr{apply(i,o){let l=a.apply([s]),u=new Tp().apply([s]),c=a.apply([s*2]);return J3(J3(l,u),c)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return W(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new V(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,c;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let h=jr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,i[0])),h=se(h,jr(r,this.recurrentKernel.read())),this.useBias&&(h=Hr(h,this.bias.read()));let[d,p,f,m]=Wt(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),u=se(P(l,a),P(o,this.activation.apply(f))),c=this.recurrentActivation.apply(m);let A=P(c,this.activation.apply(u));return[A,A,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Xa(this.activation),recurrentActivation:Xa(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};$c.className="LSTMCell";re.registerClass($c);var yy=class extends Gr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new $c(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};yy.className="LSTM";re.registerClass(yy);var Yp=class extends Ic{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return W(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){zA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{Si(`RNNCell_${r}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(Ir(a,n));return new e({cells:r})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return PA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}LA(t)}};Yp.className="StackedRNNCells";re.registerClass(Yp);function Za(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>e7(t(),n),i=()=>Nc(s,t,r);return!a||a<=1?Gt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Gt(o.clone()))}var fne=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},ov=class extends Gr{constructor(e){if(e.unroll)throw new De("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new De("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Kt({ndim:5})]}call(e,t){return W(()=>{if(this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new V("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return W(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Ft(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){W(()=>{if(!this.stateful)throw new ca("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ft(a)):this.states_=[Ft(a)];else if(e==null)Te(this.states_),this.keptStates!=null&&(Te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ft(a)):this.states_[0]=Ft(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):Te(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new V(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Gt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],u=e[o?4:3],c=Sr(l,r[0],a,s[0],i[0]),h=Sr(u,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,c,h]:[c,h,n]]}};ov.className="ConvRNN2D";var e0=class extends $c{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Xt(this.filters,"filters"),this.kernelSize=Vl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Xt(o,"kernelSize")),this.strides=Vl(r||1,2,"strides"),this.strides.forEach(o=>Xt(o,"strides")),this.padding=a||"valid",Jn(this.padding),this.dataFormat=s||"channelsLast",Ct(this.dataFormat),this.dilationRate=Vl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Xt(o,"dilationRate"))}build(e){var t;e=ht(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;o=new(t=class extends cr{apply(c,h){let d=l.apply([u]),p=Pr([u]),f=l.apply([u*2]);return NA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return W(()=>{if(e.length!==3)throw new V(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,ae,te)=>!ae||!ae[te]?Y:P(ae[te],Y),u=l(r,o,0),c=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,b,_,x]=Wt(this.kernel.read(),i,g),[I,S,T,M]=this.useBias?Wt(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,w,I,this.padding),c=this.inputConv(c,b,S,this.padding),h=this.inputConv(h,_,T,this.padding),d=this.inputConv(d,x,M,this.padding);let[D,z,B,U]=Wt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,D),m=this.recurrentConv(m,z),A=this.recurrentConv(A,B),y=this.recurrentConv(y,U);let j=this.recurrentActivation.apply(se(u,f)),X=this.recurrentActivation.apply(se(c,m)),H=se(P(X,s),P(j,this.activation.apply(se(h,A)))),ee=P(this.recurrentActivation.apply(se(d,y)),this.activation.apply(H));return[ee,ee,H]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=fne(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=aa(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Hr(a,n,this.dataFormat):a}recurrentConv(e,t){return aa(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};e0.className="ConvLSTM2DCell";re.registerClass(e0);var gy=class extends ov{constructor(e){let t=new e0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};gy.className="ConvLSTM2D";re.registerClass(gy);var t0=class extends Ke{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 W(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Nc(()=>e7(n,this.rate,a,this.seed),()=>n,r)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};t0.className="Dropout";re.registerClass(t0);var xy=class extends t0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};xy.className="SpatialDropout1D";re.registerClass(xy);var wy=class extends Ke{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,Xt(this.units,"units"),this.activation=Ka(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Ut(e.kernelConstraint),this.biasConstraint=Ut(e.biasConstraint),this.kernelRegularizer=wt(e.kernelRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.activityRegularizer=wt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=ht(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=ht(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=V3(this.activation.getClassName()),a;return r!=null?a=jr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=jr(n,this.kernel.read()),this.bias!=null&&(a=Hr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Xa(this.activation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),biasConstraint:Vt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};wy.className="Dense";re.registerClass(wy);var _y=class extends Ke{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=ht(e);for(let t of e.slice(1))if(t==null)throw new V(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],Ha(e,1)]}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a<n.rank;++a)r.push(a);r.push(1),n=n.transpose(r)}return LQ(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};_y.className="Flatten";re.registerClass(_y);var by=class extends Ke{constructor(e){super(e);this.supportsMasking=!0,this.activation=Ka(e.activation)}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.activation.apply(n)})}getConfig(){let e={activation:Xa(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};by.className="Activation";re.registerClass(by);var vy=class extends Ke{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return W(()=>(e=Pe(e),zQ(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};vy.className="RepeatVector";re.registerClass(vy);var ky=class extends Ke{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new V("Can only specifiy one unknown dimension.");else a*=l}let i=Ha(e);if(s!==null){if(a===0||i%a!=0)throw new V(n);r[s]=i/a}else if(i!==a)throw new V(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 W(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};ky.className="Reshape";re.registerClass(ky);var Ny=class extends Ke{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=kr(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new Kt({ndim:this.dims.length+1})]}computeOutputShape(e){e=ht(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return at(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Ny.className="Permute";re.registerClass(Ny);var Iy=class extends Ke{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Pe(e),r=-1;return zu(pi(n,this.maskValue),r)}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=zu(pi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Iy.className="Masking";re.registerClass(Iy);var Sy=class extends Ke{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(ft(e.inputLength))}this.inputDim=e.inputDim,Xt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Xt(this.outputDim,"outputDim"),this.embeddingsInitializer=xt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=wt(e.embeddingsRegularizer),this.activityRegularizer=wt(e.activityRegularizer),this.embeddingsConstraint=Ut(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return W(()=>this.maskZero?(e=Pe(e),pi(e,He(e))):null)}computeOutputShape(e){if(e=ht(e),this.inputLength==null)return[...e,this.outputDim];let t=ft(this.inputLength);if(t.length!==e.length-1)throw new V(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new V(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e);return n.dtype!=="int32"&&(n=bc(n,"int32")),Q3(this.embeddings.read(),n.as1D()).reshape(ht(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Nt(this.embeddingsInitializer),embeddingsRegularizer:dt(this.embeddingsRegularizer),activityRegularizer:dt(this.activityRegularizer),embeddingsConstraint:Vt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Sy.className="Embedding";re.registerClass(Sy);var Fi=class extends Ke{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new De}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new V("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[ht(e)]),e=e,e.length<2)throw new V(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let a of e)a!=null&&a[0]!==null&&t.push(a[0]);if(t=ja(t),t.length>1)throw new V(`Can not merge tensors with different batch sizes. 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Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return W(()=>NA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new V("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),r=this.axis<0?n.length+this.axis:this.axis;for(let a of t.slice(1)){if(n[r]==null||a[r]==null){n[r]=null;break}n[r]+=a[r]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new V("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new V("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new V(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return W(()=>{let n=!0;if(t.forEach(s=>{if(s!=null){n=!1;return}}),n)return null;let r=[];for(let s=0;s<e.length;++s)t[s]==null?r.push($n(e[s]).asType("bool")):t[s].rank<e[s].rank?r.push(hn(t[s],-1)):r.push(t[s]);let a=st(r,this.axis);return pd(a,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};My.className="Concatenate";re.registerClass(My);function Dc(e,t){for(;e<0;)e+=t;return e}function mne(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new De("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new De("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return W(()=>{let i;if(r>a){i=r-a;let l=[];for(let u=0;u<i;++u)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let u=0;u<i;++u)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,u=s[1]===t.shape.length-1;o=e.matMul(t,l,u)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let u=[];for(let c=l;c<l+i;++c)u.push(c);o=o.squeeze(u)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var $y=class extends Fi{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new V(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new V(`A \`Dot\` layer must be called on exactly 2 inputs, but 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Dy=class extends Ke{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 W(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Nc(()=>Sp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Dy.className="GaussianNoise";re.registerClass(Dy);var Oy=class extends Ke{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 W(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Nc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Sp(n.shape,1,r))},()=>n,t.training||!1):n})}};Oy.className="GaussianDropout";re.registerClass(Oy);var zy=class extends Ke{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Pe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return W(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Nc(()=>{let r=Pe(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=Pa(Al(n),this.rate);o=bc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,u=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(u)},()=>Pe(e),t.training||!1)}return e})}};zy.className="AlphaDropout";re.registerClass(zy);function Oc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=J5(e,t,n,r,a,s);else if(e.rank===3)i=Q5(e,t,n,r,a,s);else if(e.rank===4)i=ex(e,t,n,r,a,s);else throw new De(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function Ane(e,t,n,r,a=.001){return W(()=>{let s=Nd(e,r),i=s.mean,o=s.variance;return[Oc(e,i,o,n,t,a),i,o]})}function yne(e,t,n,r,a=.001){return W(()=>{let s=Nd(e,r),i=s.mean,o=s.variance,l=[];for(let p of kr(0,e.rank))r.indexOf(p)!==-1?l.push(1):l.push(e.shape[p]);let u=i.reshape(l),c=o.reshape(l),h=t==null?null:t.reshape(l),d=n==null?null:n.reshape(l);return[Oc(e,u,c,d,h,a),i,o]})}function gne(e,t,n,r,a=.001){return v.arraysEqual(r.slice().sort(),kr(0,e.rank-1))?Ane(e,t,n,r,a):yne(e,t,n,r,a)}var Py=class extends Ke{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=xt(e.betaInitializer||"zeros"),this.gammaInitializer=xt(e.gammaInitializer||"ones"),this.movingMeanInitializer=xt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=xt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Ut(e.betaConstraint),this.gammaConstraint=Ut(e.gammaConstraint),this.betaRegularizer=wt(e.betaRegularizer),this.gammaRegularizer=wt(e.gammaRegularizer)}build(e){e=ht(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new V(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Kt({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return W(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=kr(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=ki(1,s);l[o]=a[o];let u=i.slice();u.sort();let c=!v.arraysEqual(u,kr(0,s).slice(0,s-1)),h=()=>{if(c){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return Oc(r,A,y,g,w,this.epsilon)}else return Oc(r,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return h();let[d,p,f]=gne(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{W(()=>{let w=1-g,b=A.read(),_=b.sub(y).mul(w);A.write(b.sub(_))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Nt(this.betaInitializer),gammaInitializer:Nt(this.gammaInitializer),movingMeanInitializer:Nt(this.movingMeanInitializer),movingVarianceInitializer:Nt(this.movingVarianceInitializer),betaRegularizer:dt(this.betaRegularizer),gammaRegularizer:dt(this.gammaRegularizer),betaConstraint:Vt(this.betaConstraint),gammaConstraint:Vt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Py.className="BatchNormalization";re.registerClass(Py);var Ly=class extends Ke{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=xt(e.betaInitializer||"zeros"),this.gammaInitializer=xt(e.gammaInitializer||"ones"),this.betaRegularizer=wt(e.betaRegularizer),this.gammaRegularizer=wt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=ht(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==ja(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Pe(e),r=n.shape,a=r.length;return W(()=>{let s=!0,{mean:i,variance:o}=Nd(n,this.axis,s),l=ki(1,a);for(let f of this.axis)l[f]=r[f];let u=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,c=u(this.gamma.read()),h=u(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),c=c.tile(p),h=h.tile(p),Oc(n,i,o,h,c,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Nt(this.betaInitializer),gammaInitializer:Nt(this.gammaInitializer),betaRegularizer:dt(this.betaRegularizer),gammaRegularizer:dt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Ly.className="LayerNormalization";re.registerClass(Ly);function xne(e,t,n){return W(()=>{if(e.rank!==4)throw new V(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new V("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=br()),n!=="channelsLast"&&n!=="channelsFirst")throw new V(`Unknown data format: ${n}. 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s==="max"?i=qu(e,t,n,o):i=Wu(e,t,n,o),a==="channelsFirst"&&(i=at(i,[0,3,1,2])),i})}function lv(e,t,n,r,a,s){return W(()=>{Ct(a),G3(s),Jn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=br()),s==null&&(s="max"),e=nv(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=lm(e,t,n,o):i=Xf(e,t,n,o),a==="channelsFirst"&&(i=at(i,[0,4,1,2,3])),i})}var uv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new V(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Xt(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new V(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Jn(this.padding),this.inputSpec=[new Kt({ndim:3})]}computeOutputShape(e){e=ht(e);let t=Sr(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return W(()=>{this.invokeCallHook(e,t),e=vc(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return La(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},By=class extends uv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),n0(e,t,n,r,a,"max")}};By.className="MaxPooling1D";re.registerClass(By);var Vy=class extends uv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),n0(e,t,n,r,a,"avg")}};Vy.className="AveragePooling1D";re.registerClass(Vy);var cv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new V(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Xt(this.poolSize,"poolSize"),Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),Jn(this.padding),this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){e=ht(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Sr(t,this.poolSize[0],this.padding,this.strides[0]),n=Sr(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return W(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Uy=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),n0(e,t,n,r,a,"max")}};Uy.className="MaxPooling2D";re.registerClass(Uy);var jy=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),n0(e,t,n,r,a,"avg")}};jy.className="AveragePooling2D";re.registerClass(jy);var hv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new V(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Xt(this.poolSize,"poolSize"),Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),Jn(this.padding),this.inputSpec=[new Kt({ndim:5})]}computeOutputShape(e){e=ht(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Sr(t,this.poolSize[0],this.padding,this.strides[0]),n=Sr(n,this.poolSize[1],this.padding,this.strides[1]),r=Sr(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return W(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Hy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),lv(e,t,n,r,a,"max")}};Hy.className="MaxPooling3D";re.registerClass(Hy);var Gy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),lv(e,t,n,r,a,"avg")}};Gy.className="AveragePooling3D";re.registerClass(Gy);var dv=class extends Ke{constructor(e){super(e);this.inputSpec=[new Kt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new De}},qy=class extends dv{constructor(e){super(e||{})}call(e,t){return W(()=>{let n=Pe(e);return kt(n,1)})}};qy.className="GlobalAveragePooling1D";re.registerClass(qy);var Xy=class extends dv{constructor(e){super(e||{})}call(e,t){return W(()=>{let n=Pe(e);return Kn(n,1)})}};Xy.className="GlobalMaxPooling1D";re.registerClass(Xy);var pv=class extends Ke{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new De}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Ky=class extends pv{call(e,t){return W(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?kt(n,[1,2]):kt(n,[2,3])})}};Ky.className="GlobalAveragePooling2D";re.registerClass(Ky);var Zy=class extends pv{call(e,t){return W(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?Kn(n,[1,2]):Kn(n,[2,3])})}};Zy.className="GlobalMaxPooling2D";re.registerClass(Zy);var fv=class extends Ke{constructor(e){super(e);this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let r=t.layer,a=Ir(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},Yy=class extends fv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=ht(e),e.length<3)throw new V(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=ht(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return W(()=>(e=Pe(e),iv((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};Yy.className="TimeDistributed";re.registerClass(Yy);function wne(e){Ii(FQ,"BidirectionalMergeMode",e)}var _ne="concat",Jy=class extends fv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Ir(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=Ir(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?_ne:e.mergeMode,wne(this.mergeMode),e.weights)throw new De("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Tn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=sv(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new V("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let u=n.map(c=>new 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i;return this.mergeMode==="concat"?i=NA([r,a]):this.mergeMode==="sum"?i=se(r,a):this.mergeMode==="ave"?i=P(.5,se(r,a)):this.mergeMode==="mul"?i=P(r,a):this.mergeMode==null&&(i=[r,a]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Si(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Si(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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EA(e)}function cQ(e){return new RA(e)}function hQ(e){return new MA(e)}function dQ(e){return new Cn(e)}function pQ(e){return new Ep(e)}function fQ(e){return new Rp(e)}function mQ(e){return new Mp(e)}function AQ(e){return new Fp(e)}function yQ(e){return new $p(e)}function gQ(e){return new Dp(e)}function xQ(e){return new FA(e)}var 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Kee=0;function c7(){return Kee++}var Op={};function zp(e=""){return e in Op||(Op[e]=0),Op[e]+=1,e+Op[e].toString()}function zA(e){return Array.isArray(e)&&Array.isArray(e[0])}function Pp(e){return e.length===0?[]:Array.isArray(e[0])?e:[e]}function Pe(e){let t;if(Array.isArray(e)){if(e.length!==1)throw new W(`Expected Tensor length to be 1; got ${e.length}`);t=e[0]}else t=e;return t}function ct(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(e.length===1)return e=e,e[0];throw new W(`Expected exactly 1 Shape; got ${e.length}`)}else return e}function Lp(e){let t=0;for(let n of e)n.shape.length===0?t+=1:t+=n.shape.reduce((r,a)=>r*a);return t}var h7="Variable",d7=class{constructor(e,t="float32",n=h7,r=!0,a=null){this.dtype=t==null?"float32":t,this.shape=e.shape,this.id=c7(),n=n==null?h7:n,this.originalName=Z3(n),this.name=Y3(this.originalName),this.trainable_=r,this.constraint=a,this.val=kx(e,this.trainable_,this.name,this.dtype)}read(){return this.assertNotDisposed(),this.val}write(e){return this.assertNotDisposed(),Zee(this.val,e),this.val.id!==e.id&&(this.val.assign(e),this.constraint!=null&&this.val.assign(this.constraint.apply(this.val))),this}dispose(){this.assertNotDisposed(),this.val.dispose()}assertNotDisposed(){if(this.val.isDisposed)throw new Error(`LayersVariable ${this.name} is already disposed.`)}get trainable(){return this.trainable_}set trainable(e){this.trainable_=e,this.val.trainable=e}};function Zee(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function PA(e){return e.map(t=>t.read())}function LA(e){e.forEach(t=>{t[0].write(t[1])})}var 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this.inboundLayers)t!=null?e.push(t.name):e.push(null);return{outboundLayer:this.outboundLayer?this.outboundLayer.name:null,inboundLayers:e,nodeIndices:this.nodeIndices,tensorIndices:this.tensorIndices}}},Jee=0,Ke=class extends re.Serializable{constructor(e={}){super();this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=Jee++,this.activityRegularizer=null,this.inputSpec=null,this.supportsMasking=!1,this._trainableWeights=[],this._nonTrainableWeights=[],this._losses=[],this._updates=[],this._built=!1,this.inboundNodes=[],this.outboundNodes=[];let t=e.name;if(!t){let n=this.getClassName();t=ha(n)+"_"+zp(n)}if(this.name=t,this.trainable_=e.trainable==null?!0:e.trainable,e.inputShape!=null||e.batchInputShape!=null){let n;if(e.batchInputShape!=null)n=e.batchInputShape;else if(e.inputShape!=null){let a=null;e.batchSize!=null&&(a=e.batchSize),n=[a].concat(e.inputShape)}this.batchInputShape=n;let r=e.dtype;r==null&&(r=e.inputDType),r==null&&(r="float32"),this.dtype=r}e.weights!=null?this.initialWeights=e.weights:this.initialWeights=null,this._refCount=null,this.fastWeightInitDuringBuild=!1}static nodeKey(e,t){return e.name+"_ib-"+t.toString()}getNodeAtIndex(e,t){if(this.inboundNodes.length===0)throw new vr(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new W(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return Tn(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return Tn(this.getNodeAtIndex(e,"output").outputTensors)}get input(){if(this.inboundNodes.length>1)throw new ca(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer input" is ill-defined. 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Input received: ${e}`);for(let n=0;n<e.length;n++){let r=e[n],a=t[n];if(a==null)continue;let s=r.rank;if(a.ndim!=null&&s!==a.ndim)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${a.ndim}, found ndim=${s}`);if(a.maxNDim!=null&&s>a.maxNDim)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${a.maxNDim}, found ndim=${s}`);if(a.minNDim!=null&&s<a.minNDim)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected min_ndim=${a.minNDim}, found ndim=${s}.`);if(a.dtype!=null&&r.dtype!==a.dtype)throw new W(`Input ${n} is incompatible with layer ${this.name} : expected dtype=${a.dtype}, found dtype=${r.dtype}.`);if(a.axes){let i=r.shape;for(let o in a.axes){let l=Number(o),c=a.axes[o],u=l>=0?i[l]:i[i.length+l];if(c!=null&&[c,null].indexOf(u)===-1)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${c} but got shape ${i}.`)}}if(a.shape!=null)for(let i=0;i<a.shape.length;++i){let o=a.shape[i],l=r.shape[i];if(o!=null&&l!=null&&o!==l)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected shape=${a.shape}, found shape=${r.shape}.`)}}}call(e,t){return e}invokeCallHook(e,t){this._callHook!=null&&this._callHook(e,t)}setCallHook(e){this._callHook=e}clearCallHook(){this._callHook=null}apply(e,t){t=t||{},this.assertNotDisposed();let n=pt(e),r=!0;for(let s of n)if(!(s instanceof Ir)){r=!1;break}let a=!0;for(let s of n)if(s instanceof Ir){a=!1;break}if(r===a)throw new W("Arguments to apply() must be all SymbolicTensors or all Tensors");return Si(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let s=[];for(let i of pt(e))s.push(i.shape);this.build(Tn(s)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),this._refCount===null&&a&&(this._refCount=1)}if(this.assertInputCompatibility(e),a){let s=this.call(e,t),i=pt(s),o=[];for(let l of i)n.indexOf(l)!==-1&&(l=l.clone()),o.push(l);if(s=Tn(o),this.activityRegularizer!=null)throw new De("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return s}else{let s=Qee(e),i=this.computeOutputShape(s),o,l=ete(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?s[0]:s),i!=null&&i.length>0&&Array.isArray(i[0])?o=i.map((c,u)=>new Ir(l,c,this,pt(e),t,this.name,u)):o=new Ir(l,i,this,pt(e),t,this.name),this.addInboundNode(e,o,null,null,s,i,t),this._refCount++,this.activityRegularizer!=null)throw new De("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return o}})}warnOnIncompatibleInputShape(e){if(this.batchInputShape!=null)if(e.length!==this.batchInputShape.length)console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(e)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);else{let t=!1;this.batchInputShape.forEach((n,r)=>{n!=null&&e[r]!=null&&e[r]!==n&&(t=!0)}),t&&console.warn(`The shape of the input tensor (${JSON.stringify(e)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`)}}get outputShape(){if(this.inboundNodes==null||this.inboundNodes.length===0)throw new ca(`The layer ${this.name} has never been called and thus has no defined output shape.`);let e=[];for(let t of this.inboundNodes){let n=JSON.stringify(t.outputShapes);e.indexOf(n)===-1&&e.push(n)}if(e.length===1){let t=this.inboundNodes[0].outputShapes;return Array.isArray(t)&&Array.isArray(t[0])&&t.length===1?t[0]:t}else throw new ca(`The layer ${this.name} has multiple inbound nodes with different output shapes. Hence the notion of "output shape" is ill-defined for the layer.`)}countParams(){if(!this.built)throw new vr(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return Lp(this.weights)}build(e){this.built=!0}getWeights(e=!1){return PA(e?this.trainableWeights:this.weights)}setWeights(e){L(()=>{let t=this.weights;if(t.length!==e.length)throw new W(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. 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a=R7(e[0],t);n=a.sorted,r=a.recipientMap}else{let a=new Set;for(let s of e){let{sorted:i,recipientMap:o}=R7(s,t);for(let l of i)a.has(l.name)||(n.push(l),a.add(l.name));for(let l in o)r[l]==null&&(r[l]=new Set),o[l].forEach(c=>r[l].add(c))}}return{sorted:n,recipientCounts:Rte(r)}}function Rte(e){let t={};for(let n in e)t[n]=e[n].size;return t}function R7(e,t){let n=new Set,r=[],a={};for(let o of t.names())n.add(o);let s=[],i=[];for(s.push(e);s.length>0;){let o=s[s.length-1];if(n.has(o.name)){s.pop();continue}let l=i[i.length-1]===s.length-1;if(o.inputs.length===0||l)s.pop(),r.push(o),n.add(o.name),l&&i.pop();else{i.push(s.length-1);for(let c of o.inputs)a[c.name]==null&&(a[c.name]=new Set),a[c.name].add(o.name),!n.has(c.name)&&s.push(c)}}return{sorted:r,recipientMap:a}}function Ete(e){let t;if(e.sourceLayer.inboundNodes.length===1)t=e.sourceLayer.output;else{let n=null;for(let r=0;r<e.sourceLayer.inboundNodes.length;++r)for(let a of e.sourceLayer.inboundNodes[r].outputTensors)if(a.id===e.id){n=r;break}t=e.sourceLayer.getOutputAt(n)}return t}var qr=class extends Ke{constructor(e){super({});if(this.containerNodes=new Set,this.name=e.name,this.name==null){let y=this.getClassName().toLowerCase();this.name=zp(y)}if(this.supportsMasking=!1,this.trainable_=!0,Array.isArray(e.inputs)?this.inputs=e.inputs.slice():this.inputs=[e.inputs],Array.isArray(e.outputs)?this.outputs=e.outputs.slice():this.outputs=[e.outputs],ja(this.inputs).length!==this.inputs.length)throw new W(`The list of inputs passed to the model is redundant. 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Layer names: `+JSON.stringify(A))}this.outboundNodes=[],this.inboundNodes=[],new Wp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:this.inputs.map(y=>null),outputMasks:this.outputs.map(y=>null),inputShapes:this.inputs.map(y=>y.shape),outputShapes:this.outputs.map(y=>y.shape)}),this.built=!0,this._refCount=1}assertNotDisposed(){if(this._refCount===0)throw new Error(`Container '${this.name}' is already disposed.`)}dispose(){this.assertNotDisposed();let e={refCountAfterDispose:null,numDisposedVariables:0};if(--this._refCount==0){for(let t of this.layers)e.numDisposedVariables+=t.dispose().numDisposedVariables;for(let t of this.internalContainerRefs)e.numDisposedVariables+=t.dispose().numDisposedVariables}return e.refCountAfterDispose=this._refCount,e}get trainable(){return this.trainable_}set trainable(e){this.layers.forEach(t=>{t._trainableWeights.forEach(n=>n.trainable=e)}),this.trainable_=e}get trainableWeights(){if(this._trainableWeights.length>0)throw new W("Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. 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They will not be included in the serialized model (and thus will be missing at deserialization time).`),p={}}if(h.inboundLayers.length>0){let f=[];for(let m=0;m<h.inboundLayers.length;m++){let A=h.inboundLayers[m],y=h.nodeIndices[m],g=h.tensorIndices[m],w=qr.nodeKey(A,y),b=t[w];b==null&&(b=0),f.push([A.name,b,g,p])}l.push(f)}}}let c={};c.name=s.name,c.className=i,c.config=o,c.inboundNodes=l,n.push(c)}e.layers=n;let r=[];for(let s=0;s<this.inputLayers.length;s++){let i=this.inputLayers[s],o=this.inputLayersNodeIndices[s],l=qr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.inputLayersTensorIndices[s];r.push([i.name,c,u])}e.inputLayers=r;let a=[];for(let s=0;s<this.outputLayers.length;s++){let i=this.outputLayers[s],o=this.outputLayersNodeIndices[s],l=qr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let c=t[l];c==null&&(c=0);let u=this.outputLayersTensorIndices[s];a.push([i.name,c,u])}return e.outputLayers=a,e}static fromConfig(e,t,n={},r=!1){let a={},s={};function i(m,A){m.name in s?s[m.name].push(A):s[m.name]=[A]}function o(m,A){let y=[],g;for(let w of A){let b=w[0],_=w[1],x=w[2];if(g=w[3]==null?{}:w[3],!(b in a)){i(m,A);return}let N=a[b];if(N.inboundNodes.length<=_){i(m,A);return}let T=N.inboundNodes[_];y.push(T.outputTensors[x])}y.length>0&&m.apply(Tn(y),g)}function l(m){let A=m.name,y=Nr(m,t.customObjects!=null?t.customObjects:{});y.setFastWeightInitDuringBuild(r),a[A]=y,m.inboundNodes.forEach(g=>{if(!(g instanceof Array))throw new W(`Corrupted configuration, expected array for nodeData: ${g}`);i(y,g)})}let c=t.name,u=t.layers;for(let m of u)l(m);for(;!rQ(s);)for(let m of u){let A=a[m.name];if(A.name in s){let y=s[A.name];delete s[A.name];for(let g of y)o(A,g)}}let h=[],d=[],p=t.inputLayers;for(let m of p){let A=m[0],y=m[1],g=m[2];Ur(A in a);let w=a[A].inboundNodes[y].outputTensors;h.push(w[g])}let f=t.outputLayers;for(let m of f){let A=m[0],y=m[1],g=m[2];Ur(A in a);let w=a[A].inboundNodes[y].outputTensors;d.push(w[g])}return new e({inputs:h,outputs:d,name:c})}get stateful(){if(this._stateful)throw new W("Container instance unexpectedly has _stateful = true. 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this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};Bl.className="Sequential";re.registerClass(Bl);function Yte(e){return new da(e)}function Jte(e){return new Bl(e)}function Qte(e,t){return t==null&&(t={}),Kte(e,t)}function s7(e){return f7(e)}function ene(e,t){hr.registerCallbackConstructor(e,t)}var Ln=class extends re.Serializable{getConfig(){return{}}},V7=class extends Ln{apply(e,t=1){return MQ(e,t)}};V7.className="elu";re.registerClass(V7);var U7=class extends Ln{apply(e){return Rd(e)}};U7.className="selu";re.registerClass(U7);var j7=class extends Ln{apply(e){return Lr(e)}};j7.className="relu";re.registerClass(j7);var H7=class extends Ln{apply(e){return L(()=>ml(6,Lr(e)))}};H7.className="relu6";re.registerClass(H7);var G7=class extends Ln{apply(e){return e}};G7.className="linear";re.registerClass(G7);var q7=class extends Ln{apply(e){return 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t.className=e,t.config={},ey(t)}else return e instanceof Ln?e:ey(e)}function ty(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var ev=class extends re.Serializable{},Mc=class extends ev{constructor(e){super();ty(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return L(()=>{let t=Mt([1]);return this.hasL1&&(t=se(t,Ce(O(this.l1,Pt(e))))),this.hasL2&&(t=se(t,Ce(O(this.l2,Ic(e))))),t.asScalar()})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Mc.className="L1L2";re.registerClass(Mc);function tne(e){return ty(e),new Mc({l1:e!=null?e.l1:null,l2:0})}function nne(e){return ty(e),new Mc({l2:e!=null?e.l2:null,l1:0})}var tv={l1l2:"L1L2"};function ht(e){return mA(e)}function nv(e,t={}){return wc(e,re.SerializationMap.getMap().classNameMap,t,"regularizer")}function xt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in tv?tv[e]:e,config:{}};return nv(t)}else return e instanceof ev?e:nv(e)}var ny=class extends Ke{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Pe(e);let n=Lr(e);return this.maxValue!=null&&(n=vn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};ny.className="ReLU";re.registerClass(ny);var ry=class extends Ke{constructor(e){super(e==null?{}:e);this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Pe(e);return Gu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};ry.className="LeakyReLU";re.registerClass(ry);var ay=class extends Ke{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=gt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=xt(e.alphaRegularizer),this.alphaConstraint=Ut(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new W(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=ct(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let r of this.sharedAxes)t[r-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let r=1;r<e.length;++r)n[r]=e[r];this.inputSpec=[new Kt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Pe(e),Zu(e,this.alpha.read())}getConfig(){let e={alphaInitializer:It(this.alphaInitializer),alphaRegularizer:ht(this.alphaRegularizer),alphaConstraint:Vt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};ay.className="PReLU";re.registerClass(ay);var sy=class extends Ke{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new De(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Pe(e);return hl(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};sy.className="ELU";re.registerClass(sy);var iy=class extends Ke{constructor(e){super(e==null?{}:e);this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=Pe(e);return n.mul(vc(n.greater(this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};iy.className="ThresholdedReLU";re.registerClass(iy);var oy=class extends Ke{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new QA().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};oy.className="Softmax";re.registerClass(oy);function Vl(e,t,n){if(typeof e=="number")return ki(e,t);if(e.length!==t)throw new W(`The ${n} argument must be an integer or tuple of ${t} integers. 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instead`);if(s==="channelsFirst"&&(e=rt(e,[0,2,1])),a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=Ad(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Hr(o,n)),o})}function av(e,t,n,r=[1,1],a="valid",s,i,o=null){return L(()=>{if(s==null&&(s=_r()),Ct(s),e.rank!==3&&e.rank!==4)throw new W(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new W(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=ly(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Wa.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=rt(l,[0,3,1,2])),l})}function ane(e,t,n,r=[1,1,1],a="valid",s,i){return L(()=>{if(s==null&&(s=_r()),Ct(s),e.rank!==4&&e.rank!==5)throw new W(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new W(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=rv(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=Yf(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Hr(o,n)),s==="channelsFirst"&&(o=rt(o,[0,4,1,2,3])),o})}var uy=class extends Ke{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",uy.verifyArgs(t),this.rank=e,Xt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new De(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Vl(t.kernelSize,e,"kernelSize"),this.strides=Vl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Jn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Ct(this.dataFormat),this.activation=Ka(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=gt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Ut(t.biasConstraint),this.biasRegularizer=xt(t.biasRegularizer),this.activityRegularizer=xt(t.activityRegularizer),this.dilationRate=Vl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new W(`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 W(`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 W(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Ur("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!yA(e.kernelSize,"number",1,3))throw new W(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:Xa(this.activation),useBias:this.useBias,biasInitializer:It(this.biasInitializer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),biasConstraint:Vt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Fc=class extends uy{constructor(e,t){super(e,t);this.kernel=null,Fc.verifyArgs(t),this.filters=t.filters,Xt(this.filters,"filters"),this.kernelInitializer=gt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Ut(t.kernelConstraint),this.kernelRegularizer=xt(t.kernelRegularizer)}build(e){e=ct(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new W(`The channel dimension of the input should be defined. 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Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Kt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return L(()=>{let n=Pe(e);if(n.shape.length!==4)throw new W(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],c=this.kernelSize[0],u=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=Kp(o,h,c,this.padding),f=Kp(l,d,u,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=rt(n,[0,2,3,1]));let A=yd(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=rt(A,[0,3,1,2])),this.bias!=null&&(A=Hr(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=ct(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=Kp(t[r],o,s,this.padding),t[a]=Kp(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};cy.className="Conv2DTranspose";re.registerClass(cy);var sv=class extends Fc{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 W("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new W("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 W(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=gt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=xt(t.depthwiseRegularizer),this.depthwiseConstraint=Ut(t.depthwiseConstraint),this.pointwiseInitializer=gt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=xt(t.pointwiseRegularizer),this.pointwiseConstraint=Ut(t.pointwiseConstraint)}build(e){if(e=ct(e),e.length<this.rank+2)throw new W(`Inputs to SeparableConv${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 W(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Kt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return L(()=>{e=Pe(e);let n;if(this.rank===1)throw new De("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=rt(e,[0,2,3,1])),n=mm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=rt(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=It(this.depthwiseInitializer),e.pointwiseInitializer=It(this.pointwiseInitializer),e.depthwiseRegularizer=ht(this.depthwiseRegularizer),e.pointwiseRegularizer=ht(this.pointwiseRegularizer),e.depthwiseConstraint=Vt(this.depthwiseConstraint),e.pointwiseConstraint=Vt(this.pointwiseConstraint),e}};sv.className="SeparableConv";var hy=class extends sv{constructor(e){super(2,e)}};hy.className="SeparableConv2D";re.registerClass(hy);var Yp=class extends Fc{constructor(e){super(1,e);Yp.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"&&!yA(e.kernelSize,"number",1,1))throw new W(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Yp.className="Conv1D";re.registerClass(Yp);var dy=class extends Ke{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 L(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=Sp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Sp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Sp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Sp(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}};dy.className="Cropping2D";re.registerClass(dy);var py=class extends Ke{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,Ct(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,IQ(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 L(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=rt(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return rt(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};py.className="UpSampling2D";re.registerClass(py);function sne(e,t,n=[1,1],r="valid",a,s){return L(()=>{a==null&&(a=_r()),Ct(a);let i=ly(e,a);if(e.rank!==4)throw new W(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new W(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=cl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=rt(i,[0,3,1,2])),i})}var fy=class extends uy{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=gt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Ut(e.depthwiseConstraint),this.depthwiseRegularizer=xt(e.depthwiseRegularizer)}build(e){if(e=ct(e),e.length<4)throw new W(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new W(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${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 L(()=>{e=Pe(e);let n=sne(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=ct(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Sr(t,this.kernelSize[0],this.padding,this.strides[0]),s=Sr(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=It(this.depthwiseInitializer),e.depthwiseRegularizer=ht(this.depthwiseRegularizer),e.depthwiseConstraint=Vt(this.depthwiseRegularizer),e}};fy.className="DepthwiseConv2D";re.registerClass(fy);function iv(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new W("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function ov(e,t,n,r=!1,a,s,i=!1,o=!1){return L(()=>{let l=t.shape.length;if(l<3)throw new W(`Input should be at least 3D, but is ${l}D.`);let c=[1,0].concat(kr(2,l));if(t=rt(t,c),s!=null)throw new De("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=hn(a,-1)),a=rt(a,c)),r&&(t=Dn(t,0),a!=null&&(a=Dn(a,0)));let u=[],h,d=n,p=t.shape[0],f=or(t),m;a!=null&&(m=or(a));for(let y=0;y<p;++y){let g=f[y],w=L(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let b=L(()=>{let _=m[y],x=$n(_).sub(_),N=w[0].mul(_).add(d[0].mul(x)),T=d.map((C,F)=>w[1][F].mul(_).add(C.mul(x)));return{output:N,newStates:T}});h=b.output,d=b.newStates}o&&u.push(h)}let A;return o&&(A=dn(u,1)),[h,A,d]})}var Gr=class extends Ke{constructor(e){super(e);let t;if(e.cell==null)throw new W("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Jp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new W("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 Kt({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 kr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){zA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return L(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new De("Constants support is not implemented in RNN yet.");zA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Kt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new De("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new W(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Kt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){L(()=>{if(!this.stateful)throw new ca("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new W("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=>Mt([n,r])):this.states_=[Mt([n,this.cell.stateSize])];else if(e==null)Te(this.states_),this.keptStates!=null&&(Te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Mt([n,r])):this.states_[0]=Mt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new W(`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()):Te(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new W(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Gt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=iv(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Kt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof Ir){let o=[e].concat(s),l=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=l;let u=super.apply(o,t);return this.inputSpec=c,u}else return super.apply(e,t)}call(e,t){return L(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new W(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=ov((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],c=o[1],u=o[2];this.stateful&&this.resetStates(u,r);let h=this.returnSequences?c:l;return this.returnState?[h].concat(u):h})}getInitialState(e){return L(()=>{let t=Mt(e.shape);return t=Ce(t,[1,2]),t=kc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?vA(t,[1,n]):t):this.cell.stateSize>1?[vA(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()===Gr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=Nr(r,n);return new e(Object.assign(t,{cell:a}))}};Gr.className="RNN";re.registerClass(Gr);var Sc=class extends Ke{},Qp=class extends Sc{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,Xt(this.units,"units"),this.activation=Ka(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ct(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 L(()=>{if(e=e,e.length!==2)throw new W(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=jr(O(e,s),this.kernel.read()):a=jr(e,this.kernel.read()),this.bias!=null&&(a=Hr(a,this.bias.read())),i!=null&&(n=O(n,i));let o=se(a,jr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Xa(this.activation),useBias:this.useBias,kernelInitializer:It(this.kernelInitializer),recurrentInitializer:It(this.recurrentInitializer),biasInitializer:It(this.biasInitializer),kernelRegularizer:ht(this.kernelRegularizer),recurrentRegularizer:ht(this.recurrentRegularizer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};Qp.className="SimpleRNNCell";re.registerClass(Qp);var my=class extends Gr{constructor(e){e.cell=new Qp(e),super(e)}call(e,t){return L(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};my.className="SimpleRNN";re.registerClass(my);var e0=class extends Sc{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 W("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ka(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ct(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 L(()=>{if(e=e,e.length!==2)throw new W(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=O(e,a[0]));let c=jr(e,this.kernel.read());this.useBias&&(c=Hr(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=O(r,s[0]));let u=this.recurrentKernel.read(),[h,d]=Wt(u,[2*this.units,this.units],u.rank-1),p=jr(r,h),[f,m,A]=Wt(c,3,c.rank-1),[y,g]=Wt(p,2,p.rank-1);i=this.recurrentActivation.apply(se(f,y)),o=this.recurrentActivation.apply(se(m,g));let w=jr(O(o,r),d);l=this.activation.apply(se(A,w));let b=se(O(i,r),O(se(1,vt(i)),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:It(this.kernelInitializer),recurrentInitializer:It(this.recurrentInitializer),biasInitializer:It(this.biasInitializer),kernelRegularizer:ht(this.kernelRegularizer),recurrentRegularizer:ht(this.recurrentRegularizer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};e0.className="GRUCell";re.registerClass(e0);var Ay=class extends Gr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new e0(e),super(e)}call(e,t){return L(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ay.className="GRU";re.registerClass(Ay);var Dc=class extends Sc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ka(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=ct(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends cr{apply(i,o){let l=a.apply([s]),c=new Cp().apply([s]),u=a.apply([s*2]);return Q3(Q3(l,c),u)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return L(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new W(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,c,u;0<this.dropout&&this.dropout<1&&(e=O(e,s[0]));let h=jr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=O(r,i[0])),h=se(h,jr(r,this.recurrentKernel.read())),this.useBias&&(h=Hr(h,this.bias.read()));let[d,p,f,m]=Wt(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),c=se(O(l,a),O(o,this.activation.apply(f))),u=this.recurrentActivation.apply(m);let A=O(u,this.activation.apply(c));return[A,A,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Xa(this.activation),recurrentActivation:Xa(this.recurrentActivation),useBias:this.useBias,kernelInitializer:It(this.kernelInitializer),recurrentInitializer:It(this.recurrentInitializer),biasInitializer:It(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:ht(this.kernelRegularizer),recurrentRegularizer:ht(this.recurrentRegularizer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Dc.className="LSTMCell";re.registerClass(Dc);var yy=class extends Gr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Dc(e),super(e)}call(e,t){return L(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};yy.className="LSTM";re.registerClass(yy);var Jp=class extends Sc{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return L(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){zA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{Si(`RNNCell_${r}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(Nr(a,n));return new e({cells:r})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return PA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}LA(t)}};Jp.className="StackedRNNCells";re.registerClass(Jp);function Za(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>t7(t(),n),i=()=>Nc(s,t,r);return!a||a<=1?Gt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Gt(o.clone()))}var ine=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},lv=class extends Gr{constructor(e){if(e.unroll)throw new De("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new De("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Kt({ndim:5})]}call(e,t){return L(()=>{if(this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new W("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return L(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Mt(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){L(()=>{if(!this.stateful)throw new ca("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new W("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Mt(a)):this.states_=[Mt(a)];else if(e==null)Te(this.states_),this.keptStates!=null&&(Te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Mt(a)):this.states_[0]=Mt(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new W(`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()):Te(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new W(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Gt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],c=e[o?4:3],u=Sr(l,r[0],a,s[0],i[0]),h=Sr(c,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,u,h]:[u,h,n]]}};lv.className="ConvRNN2D";var t0=class extends Dc{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Xt(this.filters,"filters"),this.kernelSize=Vl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Xt(o,"kernelSize")),this.strides=Vl(r||1,2,"strides"),this.strides.forEach(o=>Xt(o,"strides")),this.padding=a||"valid",Jn(this.padding),this.dataFormat=s||"channelsLast",Ct(this.dataFormat),this.dilationRate=Vl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Xt(o,"dilationRate"))}build(e){var t;e=ct(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new W(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;o=new(t=class extends cr{apply(u,h){let d=l.apply([c]),p=Pr([c]),f=l.apply([c*2]);return IA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return L(()=>{if(e.length!==3)throw new W(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,ae,te)=>!ae||!ae[te]?Y:O(ae[te],Y),c=l(r,o,0),u=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,b,_,x]=Wt(this.kernel.read(),i,g),[N,T,C,F]=this.useBias?Wt(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,w,N,this.padding),u=this.inputConv(u,b,T,this.padding),h=this.inputConv(h,_,C,this.padding),d=this.inputConv(d,x,F,this.padding);let[z,B,V,U]=Wt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,z),m=this.recurrentConv(m,B),A=this.recurrentConv(A,V),y=this.recurrentConv(y,U);let j=this.recurrentActivation.apply(se(c,f)),X=this.recurrentActivation.apply(se(u,m)),G=se(O(X,s),O(j,this.activation.apply(se(h,A)))),ee=O(this.recurrentActivation.apply(se(d,y)),this.activation.apply(G));return[ee,ee,G]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=ine(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=aa(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Hr(a,n,this.dataFormat):a}recurrentConv(e,t){return aa(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};t0.className="ConvLSTM2DCell";re.registerClass(t0);var gy=class extends lv{constructor(e){let t=new t0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};gy.className="ConvLSTM2D";re.registerClass(gy);var n0=class extends Ke{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 L(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Nc(()=>t7(n,this.rate,a,this.seed),()=>n,r)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};n0.className="Dropout";re.registerClass(n0);var xy=class extends n0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};xy.className="SpatialDropout1D";re.registerClass(xy);var wy=class extends Ke{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,Xt(this.units,"units"),this.activation=Ka(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Ut(e.kernelConstraint),this.biasConstraint=Ut(e.biasConstraint),this.kernelRegularizer=xt(e.kernelRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.activityRegularizer=xt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=ct(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=ct(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=U3(this.activation.getClassName()),a;return r!=null?a=jr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=jr(n,this.kernel.read()),this.bias!=null&&(a=Hr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Xa(this.activation),useBias:this.useBias,kernelInitializer:It(this.kernelInitializer),biasInitializer:It(this.biasInitializer),kernelRegularizer:ht(this.kernelRegularizer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),biasConstraint:Vt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};wy.className="Dense";re.registerClass(wy);var by=class extends Ke{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=ct(e);for(let t of e.slice(1))if(t==null)throw new W(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],Ha(e,1)]}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a<n.rank;++a)r.push(a);r.push(1),n=n.transpose(r)}return RQ(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};by.className="Flatten";re.registerClass(by);var _y=class extends Ke{constructor(e){super(e);this.supportsMasking=!0,this.activation=Ka(e.activation)}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.activation.apply(n)})}getConfig(){let e={activation:Xa(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};_y.className="Activation";re.registerClass(_y);var vy=class extends Ke{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return L(()=>(e=Pe(e),CQ(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};vy.className="RepeatVector";re.registerClass(vy);var ky=class extends Ke{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new W("Can only specifiy one unknown dimension.");else a*=l}let i=Ha(e);if(s!==null){if(a===0||i%a!=0)throw new W(n);r[s]=i/a}else if(i!==a)throw new W(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 L(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};ky.className="Reshape";re.registerClass(ky);var Iy=class extends Ke{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=kr(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new Kt({ndim:this.dims.length+1})]}computeOutputShape(e){e=ct(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return rt(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Iy.className="Permute";re.registerClass(Iy);var Ny=class extends Ke{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Pe(e),r=-1;return Pu(pi(n,this.maskValue),r)}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=Pu(pi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Ny.className="Masking";re.registerClass(Ny);var Sy=class extends Ke{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(pt(e.inputLength))}this.inputDim=e.inputDim,Xt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Xt(this.outputDim,"outputDim"),this.embeddingsInitializer=gt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=xt(e.embeddingsRegularizer),this.activityRegularizer=xt(e.activityRegularizer),this.embeddingsConstraint=Ut(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return L(()=>this.maskZero?(e=Pe(e),pi(e,He(e))):null)}computeOutputShape(e){if(e=ct(e),this.inputLength==null)return[...e,this.outputDim];let t=pt(this.inputLength);if(t.length!==e.length-1)throw new W(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new W(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e);return n.dtype!=="int32"&&(n=vc(n,"int32")),e7(this.embeddings.read(),n.as1D()).reshape(ct(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:It(this.embeddingsInitializer),embeddingsRegularizer:ht(this.embeddingsRegularizer),activityRegularizer:ht(this.activityRegularizer),embeddingsConstraint:Vt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Sy.className="Embedding";re.registerClass(Sy);var Mi=class extends Ke{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new De}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new W("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[ct(e)]),e=e,e.length<2)throw new W(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let a of e)a!=null&&a[0]!==null&&t.push(a[0]);if(t=ja(t),t.length>1)throw new W(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let a=1;a<e.length;++a){let s=e[a]==null?null:e[a].slice(1);n=this.computeElementwiseOpOutputShape(n,s)}let r=e.map(a=>a.length);e.indexOf(null)===-1&&ja(r).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return L(()=>{if(e=e,this.reshapeRequired){let n=[],r=e.map(a=>a.rank);if(r.indexOf(null)===-1){let a=Ga(r);for(let s of e){let i=s.rank;for(let o=0;o<a-i;++o)s=kc(s,1);n.push(s)}return this.mergeFunction(n)}else{let a=!1;for(let o of e){let l=o.rank;if(l==null){let c=o.shape,u=c[0],h=c.slice(1).concat([u]),d=o.reshape([u].concat(Ha(c.slice(1))));d=rt(d,[1,0]),d=d.reshape(h),n.push(d),a=!0}else if(l>1){let c=kr(1,l).concat([0]);n.push(rt(o,c)),a=!0}else n.push(o)}let s=this.mergeFunction(n),i=s.rank;if(a){if(i==null){let o=s.shape,l=o.length,c=o[l-1],u=[c].concat(o.slice(0,o.length-1));s=rt(s.reshape([-1,c]),[1,0]).reshape(u)}else if(i>1){let o=[i-1].concat(kr(0,i-1));s=rt(s,o)}}return s}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);t=this.computeElementwiseOpOutputShape(t,a)}let n=[];for(let r of e)r!=null&&r[0]!==null&&n.push(r[0]);return n=ja(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return L(()=>{if(t==null)return null;if(!Array.isArray(t))throw new W("`mask` should be an Array");if(!Array.isArray(e))throw new W("`inputs` should be an Array");if(t.length!==e.length)throw new W(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(r=>r==null))return null;t=t.map(r=>r==null?r:hn(r,0));let n=t[0];for(let r=1;r<t.length-1;++r)n=ir(n,t[r]);return n})}},Ty=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=se(t,e[n]);return t})}};Ty.className="Add";re.registerClass(Ty);var Cy=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=O(t,e[n]);return t})}};Cy.className="Multiply";re.registerClass(Cy);var Ey=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=se(t,e[n]);return O(1/e.length,t)})}};Ey.className="Average";re.registerClass(Ey);var Ry=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=zr(t,e[n]);return t})}};Ry.className="Maximum";re.registerClass(Ry);var My=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=ml(t,e[n]);return t})}};My.className="Minimum";re.registerClass(My);var Fy=class extends Mi{constructor(e){super(e);this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new W("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let r of e)if(r!=null){t=!1;break}if(t)return;let n=[];for(let r=0;r<e.length;++r){let a=e[r].slice();a.splice(this.axis,1);let s=!1;for(let i of n)if(v.arraysEqual(i,a)){s=!0;break}s||n.push(a)}if(n.length>1)throw new W("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return L(()=>IA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new W("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),r=this.axis<0?n.length+this.axis:this.axis;for(let a of t.slice(1)){if(n[r]==null||a[r]==null){n[r]=null;break}n[r]+=a[r]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new W("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new W("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new W(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return L(()=>{let n=!0;if(t.forEach(s=>{if(s!=null){n=!1;return}}),n)return null;let r=[];for(let s=0;s<e.length;++s)t[s]==null?r.push($n(e[s]).asType("bool")):t[s].rank<e[s].rank?r.push(hn(t[s],-1)):r.push(t[s]);let a=at(r,this.axis);return fd(a,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Fy.className="Concatenate";re.registerClass(Fy);function Oc(e,t){for(;e<0;)e+=t;return e}function one(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new De("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new De("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return L(()=>{let i;if(r>a){i=r-a;let l=[];for(let c=0;c<i;++c)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let c=0;c<i;++c)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,c=s[1]===t.shape.length-1;o=e.matMul(t,l,c)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let c=[];for(let u=l;u<l+i;++u)c.push(u);o=o.squeeze(c)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var $y=class extends Mi{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new W(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new W(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],r;return Array.isArray(this.axes)?r=this.axes.map((a,s)=>Oc(a,e[s].shape.length)):r=[Oc(this.axes,t.shape.length),Oc(this.axes,n.shape.length)],this.normalize&&(t=Bp(t,r[0]),n=Bp(n,r[1])),one(t,n,r)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Oc(this.axes,e.length),Oc(this.axes,t.length)],n}computeOutputShape(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);t.splice(r[0],1),n.splice(r[1],1),n.splice(0,1);let a=t.concat(n);return a.length===1&&a.push(1),a}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};$y.className="Dot";re.registerClass($y);var Dy=class extends Ke{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 L(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Nc(()=>Tp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Dy.className="GaussianNoise";re.registerClass(Dy);var Oy=class extends Ke{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 L(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Nc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Tp(n.shape,1,r))},()=>n,t.training||!1):n})}};Oy.className="GaussianDropout";re.registerClass(Oy);var zy=class extends Ke{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Pe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return L(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Nc(()=>{let r=Pe(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=Pa(Al(n),this.rate);o=vc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(c)},()=>Pe(e),t.training||!1)}return e})}};zy.className="AlphaDropout";re.registerClass(zy);function zc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=Q5(e,t,n,r,a,s);else if(e.rank===3)i=ex(e,t,n,r,a,s);else if(e.rank===4)i=tx(e,t,n,r,a,s);else throw new De(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function lne(e,t,n,r,a=.001){return L(()=>{let s=Nd(e,r),i=s.mean,o=s.variance;return[zc(e,i,o,n,t,a),i,o]})}function une(e,t,n,r,a=.001){return L(()=>{let s=Nd(e,r),i=s.mean,o=s.variance,l=[];for(let p of kr(0,e.rank))r.indexOf(p)!==-1?l.push(1):l.push(e.shape[p]);let c=i.reshape(l),u=o.reshape(l),h=t==null?null:t.reshape(l),d=n==null?null:n.reshape(l);return[zc(e,c,u,d,h,a),i,o]})}function cne(e,t,n,r,a=.001){return v.arraysEqual(r.slice().sort(),kr(0,e.rank-1))?lne(e,t,n,r,a):une(e,t,n,r,a)}var Py=class extends Ke{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=gt(e.betaInitializer||"zeros"),this.gammaInitializer=gt(e.gammaInitializer||"ones"),this.movingMeanInitializer=gt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=gt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Ut(e.betaConstraint),this.gammaConstraint=Ut(e.gammaConstraint),this.betaRegularizer=xt(e.betaRegularizer),this.gammaRegularizer=xt(e.gammaRegularizer)}build(e){e=ct(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new W(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Kt({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return L(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=kr(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=ki(1,s);l[o]=a[o];let c=i.slice();c.sort();let u=!v.arraysEqual(c,kr(0,s).slice(0,s-1)),h=()=>{if(u){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return zc(r,A,y,g,w,this.epsilon)}else return zc(r,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return h();let[d,p,f]=cne(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{L(()=>{let w=1-g,b=A.read(),_=b.sub(y).mul(w);A.write(b.sub(_))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:It(this.betaInitializer),gammaInitializer:It(this.gammaInitializer),movingMeanInitializer:It(this.movingMeanInitializer),movingVarianceInitializer:It(this.movingVarianceInitializer),betaRegularizer:ht(this.betaRegularizer),gammaRegularizer:ht(this.gammaRegularizer),betaConstraint:Vt(this.betaConstraint),gammaConstraint:Vt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Py.className="BatchNormalization";re.registerClass(Py);var Ly=class extends Ke{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=gt(e.betaInitializer||"zeros"),this.gammaInitializer=gt(e.gammaInitializer||"ones"),this.betaRegularizer=xt(e.betaRegularizer),this.gammaRegularizer=xt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=ct(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==ja(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Pe(e),r=n.shape,a=r.length;return L(()=>{let s=!0,{mean:i,variance:o}=Nd(n,this.axis,s),l=ki(1,a);for(let f of this.axis)l[f]=r[f];let c=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,u=c(this.gamma.read()),h=c(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),u=u.tile(p),h=h.tile(p),zc(n,i,o,h,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:It(this.betaInitializer),gammaInitializer:It(this.gammaInitializer),betaRegularizer:ht(this.betaRegularizer),gammaRegularizer:ht(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Ly.className="LayerNormalization";re.registerClass(Ly);function hne(e,t,n){return L(()=>{if(e.rank!==4)throw new W(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new W("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=_r()),n!=="channelsLast"&&n!=="channelsFirst")throw new W(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let r;return n==="channelsFirst"?r=[[0,0],[0,0],t[0],t[1]]:r=[[0,0],t[0],t[1],[0,0]],sa(e,r)})}var Wy=class extends Ke{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?_r():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new W(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new W(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new W(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){e=ct(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return L(()=>hne(Pe(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Wy.className="ZeroPadding2D";re.registerClass(Wy);function r0(e,t,n,r,a,s){return L(()=>{Ct(a),q3(s),Jn(r),n==null&&(n=[1,1]),r==null&&(r="valid"),a==null&&(a=_r()),s==null&&(s="max"),e=ly(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=Xu(e,t,n,o):i=Bu(e,t,n,o),a==="channelsFirst"&&(i=rt(i,[0,3,1,2])),i})}function uv(e,t,n,r,a,s){return L(()=>{Ct(a),q3(s),Jn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=_r()),s==null&&(s="max"),e=rv(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=lm(e,t,n,o):i=Xf(e,t,n,o),a==="channelsFirst"&&(i=rt(i,[0,4,1,2,3])),i})}var cv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new W(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Xt(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new W(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Jn(this.padding),this.inputSpec=[new Kt({ndim:3})]}computeOutputShape(e){e=ct(e);let t=Sr(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return L(()=>{this.invokeCallHook(e,t),e=kc(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return La(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},By=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),r0(e,t,n,r,a,"max")}};By.className="MaxPooling1D";re.registerClass(By);var Vy=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),r0(e,t,n,r,a,"avg")}};Vy.className="AveragePooling1D";re.registerClass(Vy);var hv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new W(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Xt(this.poolSize,"poolSize"),Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),Jn(this.padding),this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){e=ct(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Sr(t,this.poolSize[0],this.padding,this.strides[0]),n=Sr(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return L(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Uy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),r0(e,t,n,r,a,"max")}};Uy.className="MaxPooling2D";re.registerClass(Uy);var jy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),r0(e,t,n,r,a,"avg")}};jy.className="AveragePooling2D";re.registerClass(jy);var dv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new W(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Xt(this.poolSize,"poolSize"),Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),Jn(this.padding),this.inputSpec=[new Kt({ndim:5})]}computeOutputShape(e){e=ct(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Sr(t,this.poolSize[0],this.padding,this.strides[0]),n=Sr(n,this.poolSize[1],this.padding,this.strides[1]),r=Sr(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return L(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Hy=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),uv(e,t,n,r,a,"max")}};Hy.className="MaxPooling3D";re.registerClass(Hy);var Gy=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Jn(r),uv(e,t,n,r,a,"avg")}};Gy.className="AveragePooling3D";re.registerClass(Gy);var pv=class extends Ke{constructor(e){super(e);this.inputSpec=[new Kt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new De}},qy=class extends pv{constructor(e){super(e||{})}call(e,t){return L(()=>{let n=Pe(e);return kt(n,1)})}};qy.className="GlobalAveragePooling1D";re.registerClass(qy);var Xy=class extends pv{constructor(e){super(e||{})}call(e,t){return L(()=>{let n=Pe(e);return Kn(n,1)})}};Xy.className="GlobalMaxPooling1D";re.registerClass(Xy);var fv=class extends Ke{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new De}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Ky=class extends fv{call(e,t){return L(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?kt(n,[1,2]):kt(n,[2,3])})}};Ky.className="GlobalAveragePooling2D";re.registerClass(Ky);var Zy=class extends fv{call(e,t){return L(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?Kn(n,[1,2]):Kn(n,[2,3])})}};Zy.className="GlobalMaxPooling2D";re.registerClass(Zy);var mv=class extends Ke{constructor(e){super(e);this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let r=t.layer,a=Nr(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},Yy=class extends mv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=ct(e),e.length<3)throw new W(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=ct(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return L(()=>(e=Pe(e),ov((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};Yy.className="TimeDistributed";re.registerClass(Yy);function dne(e){Ni(kQ,"BidirectionalMergeMode",e)}var pne="concat",Jy=class extends mv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Nr(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=Nr(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?pne:e.mergeMode,dne(this.mergeMode),e.weights)throw new De("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Tn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=iv(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new W("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let c=n.map(u=>new Kt({shape:u.shape}));this.forwardLayer.stateSpec=c.slice(0,l/2),this.backwardLayer.stateSpec=c.slice(l/2),i.push(...c)}if(r!=null)throw new De("Support for constants in Bidirectional layers is not implemented yet.");let o=s[0]instanceof Ir;for(let l of s)if(l instanceof Ir!==o)throw new W("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(o){let l=[e].concat(s),c=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=c;let h=super.apply(l,t);return this.inputSpec=u,h}else return super.apply(e,t)}call(e,t){return L(()=>{let n=t.initialState,r,a;if(n==null)r=this.forwardLayer.call(e,t),a=this.backwardLayer.call(e,t);else{let o=n.slice(0,n.length/2),l=n.slice(n.length/2);r=this.forwardLayer.call(e,Object.assign(t,{initialState:o})),a=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let s;this.returnState&&(Array.isArray(r)&&(s=r.slice(1).concat(a.slice(1))),r=r[0],a=a[0]),this.returnSequences&&(a=Dn(a,1));let i;return this.mergeMode==="concat"?i=IA([r,a]):this.mergeMode==="sum"?i=se(r,a):this.mergeMode==="ave"?i=O(.5,se(r,a)):this.mergeMode==="mul"?i=O(r,a):this.mergeMode==null&&(i=[r,a]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Si(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Si(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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+        ${n}, and tensor's shape is: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);let a=n===0?0:t.size/n,s=[];L(()=>{t=H(t,[1,n,a]);for(let o=0;o<e.length;++o){let l=o===0?0:r[o-1],c=[0,l,0],u=[1,e[o],a];s[o]=H(Re(t,c,u),this.elementShape)}return s});let i=[];for(let o=0;o<e.length;o++)i[o]=o;this.writeMany(i,s)}},Lc=class{constructor(e,t,n,r=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,e!=null&&e.forEach(a=>{if(n!==a.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${a.dtype}`);dr(t,a.shape,"TensorList shape mismatch: "),Gt(a)}),this.idTensor=ve(0),this.maxNumElements=r,Gt(this.idTensor)}get id(){return this.idTensor.id}copy(){return new Lc([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.id))&&t.dispose()}),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(e,t,n=-1){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(n!==-1&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);dr(e,this.elementShape,"TensorList shape mismatch: ");let r=Pc(this.elementShape,this.tensors,e);return L(()=>{let a=this.tensors.map(s=>H(s,r));return dn(a,0)})}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let n=Pc(this.elementShape,this.tensors,e),r=this.tensors.pop();return dr(r.shape,e,"TensorList shape mismatch: "),H(r,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(dr(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Gt(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${e}`);if(this.maxNumElements!==-1&&e>this.maxNumElements)throw new Error(`TensorListResize input size ${e} is greater maxNumElement ${this.maxNumElements}.`);this.tensors.length=e}getItem(e,t,n){if(n!==this.elementDtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${this.elementDtype}`);if(e<0||e>this.tensors.length)throw new Error(`Trying to access element ${e} in a list with ${this.tensors.length} elements.`);if(this.tensors[e]==null)throw new Error(`element at index ${e} is null.`);dr(this.tensors[e].shape,t,"TensorList shape mismatch: ");let r=Pc(this.elementShape,this.tensors,t);return H(this.tensors[e],r)}setItem(e,t){if(t.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t.dtype}, but list elements ${this.elementDtype}`);if(e<0||this.maxNumElements!==-1&&e>=this.maxNumElements)throw new Error(`Trying to set element ${e} in a list with max ${this.maxNumElements} elements.`);dr(this.elementShape,t.shape,"TensorList shape mismatch: "),Gt(t),this.tensors[e]=t}gather(e,t,n){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);dr(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());let r=Pc(this.elementShape,this.tensors,n);return e.length===0?xr([],[0].concat(r)):L(()=>{let a=e.map(s=>H(this.tensors[s],r));return dn(a,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);dr(this.elementShape,t,"TensorList shape mismatch: ");let n=Pc(this.elementShape,this.tensors,t);return this.size()===0?xr([],[0].concat(n)):L(()=>{let r=this.tensors.map(a=>H(a,n));return at(r,0)})}};function sre(e,t,n){let r=e.dtype;if(e.shape.length<1)throw new Error(`Tensor must be at least a vector, but saw shape: ${e.shape}`);if(e.dtype!==n)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${n}`);let a=e.shape.slice(1);dr(a,t,"TensorList shape mismatch: ");let s=or(e);return new Lc(s,t,r)}function ire(e,t,n){return new Lc([],e,t,n)}function ore(e,t,n,r){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let a=Math.max(...t);if(r!=null&&r!==-1&&a>=r)throw new Error(`Max index must be < array size (${a}  vs. ${r})`);let s=new Lc([],n,e.dtype,r),i=or(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function lre(e,t,n){let r=0,a=t.map(u=>(r+=u,r));if(r!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to
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r=k("size",e,t,n),a=k("dtype",e,t,n),s=k("elementShape",e,t,n),i=k("dynamicSize",e,t,n),o=k("clearAfterRead",e,t,n),l=k("identicalElementShapes",e,t,n),u=k("name",e,t,n),c=new dre(u,a,r,s,l,i,o);return n.addTensorArray(c),[c.idTensor,ve(1)]}case"TensorArrayWriteV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.write(a,s),[i.idTensor]}case"TensorArrayReadV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,s)]}case"TensorArrayScatterV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.scatter(a,s),[i.idTensor]}case"TensorArrayConcatV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),s=k("dtype",e,t,n);return[a.concat(s)]}case"TensorArraySplitV3":{let 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r=k("elementShape",e,t,n),a=k("elementDType",e,t,n),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,n),o=fre(r,a,i);return n.addTensorList(o),[o.idTensor]}case"TensorListGather":{let r=k("tensorListId",e,t,n),a=k("indices",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,i,s)]}case"TensorListStack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=k("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,s,i)]}case"TensorListFromTensor":{let r=k("tensor",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=pre(r,a,s);return n.addTensorList(i),[i.idTensor]}case"TensorListConcat":{let r=k("tensorListId",e,t,n),a=n.getTensorList(r.id),s=k("dtype",e,t,n),i=k("elementShape",e,t,n);return[a.concat(s,i)]}case"TensorListPushBack":{let r=k("tensorListId",e,t,n),a=k("tensor",e,t,n),s=n.getTensorList(r.id);return s.pushBack(a),[s.idTensor]}case"TensorListPopBack":{let 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p2(Bv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=Bv.Instance.transformGraph(e.modelInitializer);this.initializer=new p2(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=bn.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 je)&&!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 Tt(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. 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-`).map(e=>(e.endsWith("\r")&&(e=e.slice(0,-1)),e))}},o0='"',Lc=Symbol("out"),c6=Symbol("field"),l0=Symbol("quote"),y2=Symbol("quoteafterquote"),h6=Symbol("quoteinquote"),Qv=class extends Ul{constructor(e,t){super();this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new Jv(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((r,a)=>(r[a]=r[a]+1||1,r),{}),n=Object.keys(t).filter(r=>t[r]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let r of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(r)===-1)throw new Error('The key "'+r+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},r={};for(let a=0;a<this.fullColumnNames.length;a++){let s=this.fullColumnNames[a],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[a],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let u=Number(o);if(isNaN(u))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=u;else switch(i.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(o);break;default:l=u}}i&&i.isLabel?r[s]=l:n[s]=l}}return Object.keys(r).length===0?n:{xs:n,ys:r}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],r=0,a=e.length,s=Lc;for(let i=0;i<a;i++)switch(s){case Lc:switch(e.charAt(i)){case o0:r=i+1,s=l0;break;case this.delimiter:if(r=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=Lc;break;default:s=c6,r=i;break}break;case c6:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i)),s=Lc,r=i+1;break;default:}break;case l0:switch(e.charAt(i)){case o0:s=y2;break;default:}break;case y2:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i-1)),s=Lc,r=i+1;break;case o0:s=l0;break;default:s=h6;break}break;case h6:switch(e.charAt(i)){case o0:s=l0;break;default:}break;default:}if(s===y2?n.push(e.substring(r,a-1)):n.push(e.substring(r)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},d6=class extends Zt{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(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new d6(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(a),r({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),xr(n,t)}},p6=class extends Zt{constructor(e,t){super();if(this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=on([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=Nn([s,a,o,i],[1,4])}else this.cropBox=Nn([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new p6(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=al.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return W(()=>{let t=hn(Ae(e,"float32"),0),n;n=Ge.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return G(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},f6=class{},m6=class extends Zt{split(e){return new _ae(this,e)}},_ae=class extends m6{constructor(e,t){super();this.upstream=e,this.impl=new bae(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},bae=class extends A2{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},kae=class extends Zt{decodeUTF8(){return new vae(this)}},vae=class extends m6{constructor(e){super();this.upstream=e,this.impl=new Nae(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Nae=class extends A2{constructor(e){super();if(this.upstream=e,J().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=ck();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return J().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},A6=class extends kae{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(J().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let r=new FileReader;r.onload=s=>{let i=r.result;if(i instanceof 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$ae=[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],Dae=[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],Oae=[33,133,362,263,1,78,308],ohe=$ae.map(e=>w2[e]),lhe=Dae.map(e=>w2[e]),uhe=Oae.map(e=>w2[e]);var _2=Xr.leftEyeLower0,b2=Xr.rightEyeLower0,ql={leftBounds:[_2[0],_2[_2.length-1]],rightBounds:[b2[0],b2[b2.length-1]]},p0={count:468,mouth:13,symmetryLine:[13,Xr.midwayBetweenEyes[0]]},S6={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Xl={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function f0(e,t,n,r){for(let a=0;a<x2.length;a++){let{key:s,indices:i}=x2[a],o=Xr[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let u=i[l];e[o[l]]=[t[u][0],t[u][1],(t[u][2]+e[o[l]][2])/2]}}}var v2=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Wc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?d0(r,[0,0]):h0,l=r!==0?i.map(h=>[...I6(h,o),h[2]]):i,u=r!==0?N6(a):h0,c=[...Hl({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+Ja(c,u[0]),h[1]+Ja(c,u[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[ql.leftBounds[0]][2],r=t[ql.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=c0(u0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Wc(i),l=Ge.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&Ar.flags.IS_BROWSER&&(l=Ge.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<Xl.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],u=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],u])}return{rawCoords:s,iris:s.slice(Xl.index)}}getAdjustedIrisCoords(t,n,r){let a=t[Xr[`${r}EyeUpper0`][Xl.upperCenter]][2],s=t[Xr[`${r}EyeLower0`][Xl.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let u=i;return l===2?u=a:l===4&&(u=s),[o[0],o[1],u]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=b6({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=u0(o),u=c0(l),c=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...u,confidence:h,landmarks:c}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=W(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,u,c=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&Ar.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=p0.count?p0.symmetryLine:S6.symmetryLine;c=g2(i.landmarks[_],i.landmarks[x]);let I=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),S=[I[0]/t.shape[2],I[1]/t.shape[1]],T=Ge.rotateWithOffset(t,c,0,S);h=d0(-c,I),n.face.mesh.enabled?u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.meshSize,this.meshSize]).div(255):u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.boxSize,this.boxSize]).div(255)}else{h=h0;let _=t.clone();n.face.mesh.enabled?u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:i.confidence,confidence:i.confidence,image:u};let[,d,p]=this.meshDetector.predict(u),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=G(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:_,boxSize:x,crop:I}=this.getEyeBox(A,u,ql.leftBounds[0],ql.leftBounds[1],!0),{box:S,boxSize:T,crop:M}=this.getEyeBox(A,u,ql.rightBounds[0],ql.rightBounds[1]),z=this.irisModel.predict(st([I,M])).dataSync(),B=z.slice(0,Xl.numCoordinates*3),{rawCoords:U,iris:j}=this.getEyeCoords(B,_,x,!0),X=z.slice(Xl.numCoordinates*3),{rawCoords:H,iris:ee}=this.getEyeCoords(X,S,T),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(f0(A,U,"left",null),f0(A,H,"right",null)):Y<1?f0(A,U,"left",["EyeUpper0","EyeLower0"]):f0(A,H,"right",["EyeUpper0","EyeLower0"]);let ae=this.getAdjustedIrisCoords(A,j,"left"),te=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(ae).concat(te)}let y=this.transformRawCoords(A,i,c,h);i=u0(this.calculateLandmarksBoundingBox(y),1.5);let g=Nn(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&n.face.detector.return&&Ar.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=p0.count?p0.symmetryLine:S6.symmetryLine;c=g2(i.landmarks[_],i.landmarks[x]);let I=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),S=[I[0]/t.shape[2],I[1]/t.shape[1]],T=Ge.rotateWithOffset(t,c,0,S);h=d0(-c,I),u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.meshSize,this.meshSize]).div(255)}let w={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:u,rawCoords:A},b=c0(i);return this.storedBoxes[o]={...b,landmarks:y,confidence:i.confidence,faceConfidence:f},w}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var Ng=yh(C6());var I2={};tr(I2,{load:()=>S2,predict:()=>T2});var N2={};function pr(e,t){if(!t||!t.kernels)return;let n=5,r=t.kernels.filter(o=>o.kernelTimeMs>0).reduce((o,l)=>o+=l.kernelTimeMs,0),a=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.kernelTimeMs>0).sort((o,l)=>l.kernelTimeMs-o.kernelTimeMs),s=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.totalBytesSnapshot>0).sort((o,l)=>l.totalBytesSnapshot-o.totalBytesSnapshot);a.length>n&&(a.length=n),s.length>n&&(s.length=n);let i={newBytes:t.newBytes,newTensors:t.newTensors,peakBytes:t.peakBytes,numKernelOps:t.kernels.length,timeKernelOps:r,slowestKernelOps:a,largestKernelOps:s};N2[e]=i,Ee("Human profiler",e,i)}var Qa,m0={age:0},A0=Number.MAX_SAFE_INTEGER;async function S2(e){return Qa||(Qa=await Tt(e.face.age.modelPath),e.debug&&Ee(`load model: ${e.face.age.modelPath.match(/\/(.*)\./)[1]}`)),Qa}async function T2(e,t){return Qa?A0<t.face.age.skipFrames&&t.videoOptimized&&m0.age&&m0.age>0?(A0++,m0):(t.videoOptimized?A0=0:A0=Number.MAX_SAFE_INTEGER,new 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r=Ge.resizeBilinear(e,[ma.inputs[0].shape[2],ma.inputs[0].shape[1]],!1),a;R2?a=W(()=>{let[o,l,u]=Wt(r,3,3),c=P(o,F2[0]),h=P(l,F2[1]),d=P(u,F2[2]);return $a([c,h,d]).sub(.5).mul(2)}):a=P(r,[255]),Te(r);let s,i={gender:"",confidence:0};if(!t.profile)t.face.gender.enabled&&(s=await ma.predict(a));else{let o=t.face.gender.enabled?await qn(()=>ma.predict(a)):{};s=o.result.clone(),o.result.dispose(),pr("gender",o)}if(a.dispose(),s){let o=s.dataSync();if(R2)(o[0]>t.face.gender.minConfidence||o[1]>t.face.gender.minConfidence)&&(i.gender=o[0]>o[1]?"female":"male",i.confidence=o[0]>o[1]?Math.trunc(100*o[0])/100:Math.trunc(100*o[1])/100);else{let l=Math.trunc(200*Math.abs(o[0]-.5))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]<=.5?"female":"male",i.confidence=Math.min(.99,l))}}s.dispose(),E2=i,n(i)})):null}var D2={};tr(D2,{load:()=>P2,predict:()=>L2});var Pae=["angry","disgust","fear","happy","sad","surprise","neutral"],es,O2=[],g0=Number.MAX_SAFE_INTEGER,z2=[.2989,.587,.114];async function 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_=this.transformRawCoords(b,p,l,d),x=this.getBoxForHandLandmarks(_);this.storedBoxes[i]=x;let I={landmarks:_,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(I)}else this.storedBoxes[i]=null;y.dispose()}else{let l=v0(k0(o),Q6),u={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(u)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var t4=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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Tt(e.body.modelPath),fr.width=parseInt(fr.signature.inputs["input_1:0"].tensorShape.dim[2].size),fr.height=parseInt(fr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Ee(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),fr}async function fg(e,t){if(!fr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=Ge.resizeBilinear(e,[fr.width,fr.height],!1),a=xe(r,[255]);r.dispose();let s;if(t.profile){let u=await qn(()=>fr.predict(a));s=u.result.find(c=>c.size===195||c.size===155).dataSync(),u.result.forEach(c=>c.dispose()),pr("blazepose",u)}else{let u=await fr.predict(a);s=u.find(c=>c.size===195||c.size===155).dataSync(),u.forEach(c=>c.dispose())}a.dispose();let i=[],o=s.length===195?n4:r4,l=5;for(let u=0;u<s.length/l;u++)i.push({id:u,part:o[u],position:{x:Math.trunc(n.width*s[l*u+0]/255),y:Math.trunc(n.height*s[l*u+1]/255),z:Math.trunc(s[l*u+2])+0},score:(100-Math.trunc(100/(1+Math.exp(s[l*u+3]))))/100,presence:(100-Math.trunc(100/(1+Math.exp(s[l*u+4]))))/100});return[{keypoints:i}]}var mg={};tr(mg,{load:()=>yg,predict:()=>gg});var Cr,Ag=[],N0=Number.MAX_SAFE_INTEGER,I0=2.5,lse=["person","bicycle","car","motorcycle","airplane","bus","train","vehicle","boat","traffic light","fire hydrant","stop sign","parking meter","bench","animal","animal","animal","animal","animal","animal","animal","bear","animal","animal","backpack","umbrella","handbag","tie","suitcase","frisbee","skis","snowboard","sports ball","kite","baseball bat","baseball glove","skateboard","surfboard","tennis racket","bottle","wine glass","cup","fork","knife","spoon","bowl","banana","apple","sandwich","orange","broccoli","carrot","hot dog","pizza","pastry","cake","chair","couch","potted plant","bed","dining 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this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function Zv(e,t,n,r){let a=new Set,s=[],i=null,o=null,l=new Set,c=Object.keys(e).map(d=>Wn(d)[0]),u=[];r!=null&&(u=r.map(d=>Wn(d.name)[0]));let h=[...t];for(;h.length>0;){let d=h.pop();if((Kv(d)||Ire(d)||Nre(d))&&i==null&&(i=d,o=i.children.map(p=>p.name).filter(p=>a.has(p))),a.add(d.name),n[d.name]==null&&c.indexOf(d.name)===-1&&u.indexOf(d.name)===-1){if(d.inputs.length===0){s.push(d.name);continue}d.inputs.forEach(p=>{l.has(p.name)||(l.add(p.name),h.push(p))})}}return{inputs:e,outputs:t,usedNodes:a,missingInputs:s,dynamicNode:i,syncInputs:o}}function 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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 p2(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 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RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(let t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);let e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),n}},f2=class extends i6{constructor(){super(f2.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){let e=this.capacity*2,t=new 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uae(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new sae(this,e,t)}columnMajorBatch(e,t=!0,n=a6){return this.rowMajorBatch(e,t).map(r=>Gre(r,n))}concatenate(e,t){return new l6(o6([this,e]),t)}take(e){return e<0||e==null?this:new aae(this,e)}skip(e){return e<0||e==null?this:new rae(this,e)}prefetch(e){return new c6(this,e)}shuffle(e,t){return new cae(this,e,t)}serial(){return new nae(this)}},Yre=class extends Zt{constructor(e){super();this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:Zre(e),done:!1}}},Jre=class extends Zt{constructor(e){super();this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: 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this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},sae=class extends Zt{constructor(e,t,n=!0){super();this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},iae=class extends Zt{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Te(e.value)}}},oae=class extends Zt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=yr.getTensorsInContainer(e.value),n=this.transform(e.value),r=yr.getTensorsInContainer(n);for(let a of t)yr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},lae=class extends Zt{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},u6=class extends Zt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=yr.getTensorsInContainer(e.value),n=await this.transform(e.value),r=yr.getTensorsInContainer(n);for(let a of t)yr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},A2=class extends Zt{constructor(){super();this.outputQueue=new f2,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},uae=class extends A2{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=yr.getTensorsInContainer(e.value),n=this.transform(e.value),r=yr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let a of t)yr.isTensorInList(a,r)||a.dispose();return!0}},l6=class extends Zt{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}},Ya;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(Ya||(Ya={}));var eae=class extends Zt{constructor(e,t=Ya.FAIL){super();this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function r(s){return s instanceof Zt?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await s6(this.iterators,r);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case Ya.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case Ya.SHORTEST:return{value:null,done:!0};case Ya.LONGEST:default:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},c6=class extends Zt{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new i6(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},cae=class extends c6{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=jre.alea(n||v.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},Ul=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
+      ${e}`);let r;return this.size===Infinity||this.size==null?r=this.size:t?r=Math.ceil(this.size/e):r=Math.floor(this.size/e),Bn(async()=>(await n.iterator()).columnMajorBatch(e,t,hae),r)}concatenate(e){let t=this,n;return this.size===Infinity||e.size===Infinity?n=Infinity:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Bn(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===Infinity?n=Infinity:n=null,Bn(async()=>(await t.iterator()).filter(r=>L(()=>e(r))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Bn(async()=>(await t.iterator()).map(n=>L(()=>e(n))),this.size)}mapAsync(e){let t=this;return Bn(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Bn(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=Infinity:n=null,Bn(async()=>{let r=m2(async()=>({value:await t.iterator(),done:!1}));return Qre(r.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Bn(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let r=this,a=Ure.alea(t||v.now().toString());return Bn(async()=>{let s=a.int32();return n&&(s+=a.int32()),(await r.iterator()).shuffle(e,s.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Bn(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Ul.MAX_BUFFER_SIZE=1e4;function Bn(e,t=null){return new class extends Ul{constructor(){super(...arguments);this.size=t}async iterator(){return e()}}}function Dre(e){return Bn(async()=>o6(e),e.length)}function Ore(e){if(!jl(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Bn(async()=>{let n=await s6(e,r=>{if(r instanceof Ul)return{value:r.iterator(),recurse:!1};if(jl(r))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return tae(n,Ya.SHORTEST)},t)}function hae(e){if(e===null)return null;let t=e[0];return Xre(t)?{value:dae(e),recurse:!1}:{value:null,recurse:!0}}function dae(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof je?dn(e):xr(e)}var Qv=class extends Ul{constructor(e){super();this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
+`).map(e=>(e.endsWith("\r")&&(e=e.slice(0,-1)),e))}},l0='"',Wc=Symbol("out"),h6=Symbol("field"),u0=Symbol("quote"),y2=Symbol("quoteafterquote"),d6=Symbol("quoteinquote"),e6=class extends Ul{constructor(e,t){super();this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new Qv(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((r,a)=>(r[a]=r[a]+1||1,r),{}),n=Object.keys(t).filter(r=>t[r]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let r of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(r)===-1)throw new Error('The key "'+r+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},r={};for(let a=0;a<this.fullColumnNames.length;a++){let s=this.fullColumnNames[a],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[a],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let c=Number(o);if(isNaN(c))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=c;else switch(i.dtype){case"float32":l=c;break;case"int32":l=Math.floor(c);break;case"bool":l=this.getBoolean(o);break;default:l=c}}i&&i.isLabel?r[s]=l:n[s]=l}}return Object.keys(r).length===0?n:{xs:n,ys:r}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],r=0,a=e.length,s=Wc;for(let i=0;i<a;i++)switch(s){case Wc:switch(e.charAt(i)){case l0:r=i+1,s=u0;break;case this.delimiter:if(r=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=Wc;break;default:s=h6,r=i;break}break;case h6:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i)),s=Wc,r=i+1;break;default:}break;case u0:switch(e.charAt(i)){case l0:s=y2;break;default:}break;case y2:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i-1)),s=Wc,r=i+1;break;case l0:s=u0;break;default:s=d6;break}break;case d6:switch(e.charAt(i)){case l0:s=u0;break;default:}break;default:}if(s===y2?n.push(e.substring(r,a-1)):n.push(e.substring(r)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},p6=class extends Zt{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(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new p6(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(a),r({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),xr(n,t)}},f6=class extends Zt{constructor(e,t){super();if(this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=on([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=In([s,a,o,i],[1,4])}else this.cropBox=In([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new f6(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=al.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: 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Nae=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],Sae=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],Tae=[33,133,362,263,1,78,308],Qce=Nae.map(e=>w2[e]),ehe=Sae.map(e=>w2[e]),the=Tae.map(e=>w2[e]);var b2=Xr.leftEyeLower0,_2=Xr.rightEyeLower0,ql={leftBounds:[b2[0],b2[b2.length-1]],rightBounds:[_2[0],_2[_2.length-1]]},f0={count:468,mouth:13,symmetryLine:[13,Xr.midwayBetweenEyes[0]]},T6={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Xl={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function m0(e,t,n,r){for(let a=0;a<x2.length;a++){let{key:s,indices:i}=x2[a],o=Xr[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let c=i[l];e[o[l]]=[t[c][0],t[c][1],(t[c][2]+e[o[l]][2])/2]}}}var v2=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Bc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?p0(r,[0,0]):d0,l=r!==0?i.map(h=>[...S6(h,o),h[2]]):i,c=r!==0?N6(a):d0,u=[...Hl({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+Ja(u,c[0]),h[1]+Ja(u,c[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[ql.leftBounds[0]][2],r=t[ql.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=h0(c0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Bc(i),l=Ge.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&Ar.flags.IS_BROWSER&&(l=Ge.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<Xl.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],c=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],c])}return{rawCoords:s,iris:s.slice(Xl.index)}}getAdjustedIrisCoords(t,n,r){let a=t[Xr[`${r}EyeUpper0`][Xl.upperCenter]][2],s=t[Xr[`${r}EyeLower0`][Xl.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let c=i;return l===2?c=a:l===4&&(c=s),[o[0],o[1],c]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=v6({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=c0(o),c=h0(l),u=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...c,confidence:h,landmarks:u}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=L(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,c,u=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&Ar.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=f0.count?f0.symmetryLine:T6.symmetryLine;u=g2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],C=Ge.rotateWithOffset(t,u,0,T);h=p0(-u,N),n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},C,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},C,[this.boxSize,this.boxSize]).div(255)}else{h=d0;let _=t.clone();n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:i.confidence,confidence:i.confidence,image:c};let[,d,p]=this.meshDetector.predict(c),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=H(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:_,boxSize:x,crop:N}=this.getEyeBox(A,c,ql.leftBounds[0],ql.leftBounds[1],!0),{box:T,boxSize:C,crop:F}=this.getEyeBox(A,c,ql.rightBounds[0],ql.rightBounds[1]),B=this.irisModel.predict(at([N,F])).dataSync(),V=B.slice(0,Xl.numCoordinates*3),{rawCoords:U,iris:j}=this.getEyeCoords(V,_,x,!0),X=B.slice(Xl.numCoordinates*3),{rawCoords:G,iris:ee}=this.getEyeCoords(X,T,C),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(m0(A,U,"left",null),m0(A,G,"right",null)):Y<1?m0(A,U,"left",["EyeUpper0","EyeLower0"]):m0(A,G,"right",["EyeUpper0","EyeLower0"]);let ae=this.getAdjustedIrisCoords(A,j,"left"),te=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(ae).concat(te)}let y=this.transformRawCoords(A,i,u,h);i=c0(this.calculateLandmarksBoundingBox(y),1.5);let g=In(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&n.face.detector.return&&Ar.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=f0.count?f0.symmetryLine:T6.symmetryLine;u=g2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],C=Ge.rotateWithOffset(t,u,0,T);h=p0(-u,N),c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},C,[this.meshSize,this.meshSize]).div(255)}let w={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:c,rawCoords:A},b=h0(i);return this.storedBoxes[o]={...b,landmarks:y,confidence:i.confidence,faceConfidence:f},w}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var kg=gh(E6());var N2={};tr(N2,{load:()=>S2,predict:()=>T2});var I2={};function pr(e,t){if(!t||!t.kernels)return;let n=5,r=t.kernels.filter(o=>o.kernelTimeMs>0).reduce((o,l)=>o+=l.kernelTimeMs,0),a=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.kernelTimeMs>0).sort((o,l)=>l.kernelTimeMs-o.kernelTimeMs),s=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.totalBytesSnapshot>0).sort((o,l)=>l.totalBytesSnapshot-o.totalBytesSnapshot);a.length>n&&(a.length=n),s.length>n&&(s.length=n);let i={newBytes:t.newBytes,newTensors:t.newTensors,peakBytes:t.peakBytes,numKernelOps:t.kernels.length,timeKernelOps:r,slowestKernelOps:a,largestKernelOps:s};I2[e]=i,Ee("Human profiler",e,i)}var Qa,A0={age:0},y0=Number.MAX_SAFE_INTEGER;async function S2(e){return Qa||(Qa=await Tt(e.face.age.modelPath),e.debug&&Ee(`load model: ${e.face.age.modelPath.match(/\/(.*)\./)[1]}`)),Qa}async function T2(e,t){return Qa?y0<t.face.age.skipFrames&&t.videoOptimized&&A0.age&&A0.age>0?(y0++,A0):(t.videoOptimized?y0=0:y0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ge.resizeBilinear(e,[Qa.inputs[0].shape[2],Qa.inputs[0].shape[1]],!1),a=O(r,[255]);Te(r);let s,i={age:0};if(!t.profile)t.face.age.enabled&&(s=await Qa.predict(a));else{let o=t.face.age.enabled?await qn(()=>Qa.predict(a)):{};s=o.result.clone(),o.result.dispose(),pr("age",o)}if(a.dispose(),s){let o=s.dataSync();i.age=Math.trunc(10*o[0])/10}s.dispose(),A0=i,n(i)})):null}var C2={};tr(C2,{load:()=>F2,predict:()=>$2});var ma,E2={gender:""},g0=Number.MAX_SAFE_INTEGER,R2=!1,M2=[.2989,.587,.114];async function F2(e){return ma||(ma=await Tt(e.face.gender.modelPath),R2=ma.inputs[0].shape[3]===1,e.debug&&Ee(`load model: ${e.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),ma}async function $2(e,t){return ma?g0<t.face.gender.skipFrames&&t.videoOptimized&&E2.gender!==""?(g0++,E2):(t.videoOptimized?g0=0:g0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ge.resizeBilinear(e,[ma.inputs[0].shape[2],ma.inputs[0].shape[1]],!1),a;R2?a=L(()=>{let[o,l,c]=Wt(r,3,3),u=O(o,M2[0]),h=O(l,M2[1]),d=O(c,M2[2]);return $a([u,h,d]).sub(.5).mul(2)}):a=O(r,[255]),Te(r);let s,i={gender:"",confidence:0};if(!t.profile)t.face.gender.enabled&&(s=await ma.predict(a));else{let o=t.face.gender.enabled?await qn(()=>ma.predict(a)):{};s=o.result.clone(),o.result.dispose(),pr("gender",o)}if(a.dispose(),s){let o=s.dataSync();if(R2)(o[0]>t.face.gender.minConfidence||o[1]>t.face.gender.minConfidence)&&(i.gender=o[0]>o[1]?"female":"male",i.confidence=o[0]>o[1]?Math.trunc(100*o[0])/100:Math.trunc(100*o[1])/100);else{let l=Math.trunc(200*Math.abs(o[0]-.5))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]<=.5?"female":"male",i.confidence=Math.min(.99,l))}}s.dispose(),E2=i,n(i)})):null}var D2={};tr(D2,{load:()=>P2,predict:()=>L2});var Eae=["angry","disgust","fear","happy","sad","surprise","neutral"],es,O2=[],x0=Number.MAX_SAFE_INTEGER,z2=[.2989,.587,.114];async function P2(e){return es||(es=await Tt(e.face.emotion.modelPath),e.debug&&Ee(`load model: ${e.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),es}async function L2(e,t){return es?x0<t.face.emotion.skipFrames&&t.videoOptimized&&O2.length>0?(x0++,O2):(t.videoOptimized?x0=0:x0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ge.resizeBilinear(e,[es.inputs[0].shape[2],es.inputs[0].shape[1]],!1),[a,s,i]=Wt(r,3,3);r.dispose();let o=O(a,z2[0]),l=O(s,z2[1]),c=O(i,z2[2]);a.dispose(),s.dispose(),i.dispose();let u=$a([o,l,c]);o.dispose(),l.dispose(),c.dispose();let h=L(()=>u.sub(.5).mul(2));u.dispose();let d=[];if(t.face.emotion.enabled){let p;if(t.profile){let f=await qn(()=>es.predict(h));p=f.result.dataSync(),f.result.dispose(),pr("emotion",f)}else{let f=await es.predict(h);p=f.dataSync(),Te(f)}for(let f=0;f<p.length;f++)p[f]>t.face.emotion.minConfidence&&d.push({score:Math.min(.99,Math.trunc(100*p[f])/100),emotion:Eae[f]});d.sort((f,m)=>m.score-f.score)}h.dispose(),O2=d,n(d)})):null}var Kr;async function W2(e){return Kr||(Kr=await Tt(e.face.embedding.modelPath),e.debug&&Ee(`load model: ${e.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),Kr}function B2(e,t,n=2){if(!e||!t||(e==null?void 0:e.length)===0||(t==null?void 0:t.length)===0||(e==null?void 0:e.length)!==(t==null?void 0:t.length))return 0;let r=e.map((s,i)=>Math.abs(e[i]-t[i])**n).reduce((s,i)=>s+i,0)**(1/n);return Math.max(Math.trunc(1e3*(1-r))/1e3,0)}function R6(e,t,n=0){let r={simmilarity:0,name:"",source:"",embedding:[]};if(!e||!t||!Array.isArray(e)||!Array.isArray(t))return r;for(let a of t)if(a.embedding&&a.name){let s=B2(e,a.embedding);s>n&&s>r.simmilarity&&(r={...a,simmilarity:s})}return r}function V2(e){return L(()=>{let n=[[.05,.15,.85,.85]],r=e.image||e.tensor;if(!(r instanceof je))return null;let a=r.shape.length===3?Ge.cropAndResize(hn(r,0),n,[0],[Kr.inputs[0].shape[2],Kr.inputs[0].shape[1]]):Ge.cropAndResize(r,n,[0],[Kr.inputs[0].shape[2],Kr.inputs[0].shape[1]]),s=[.2989,.587,.114],[i,o,l]=Wt(a,3,3),c=O(i,s[0]),u=O(o,s[1]),h=O(l,s[2]),d=$a([c,u,h]),p=dn([d,d,d],3).squeeze(4),f=p.sub(p.min());return f.div(f.max())})}async function U2(e,t){return Kr?new Promise(async n=>{let r=[];if(t.face.embedding.enabled){let a=V2(e);if(!t.profile)r=L(()=>[...Kr.predict(a).reshape([128,2]).logSumExp(1).dataSync()]);else{let s=await qn(()=>Kr.predict({img_inputs:a}));r=[...s.result.dataSync()],s.result.dispose(),pr("emotion",s)}Te(a)}n(r)}):[]}var tg={};tr(tg,{PoseNet:()=>ng,load:()=>rg});function Rae(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var j2=class{constructor(t){this.model=t}predict(t){return L(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=Rae(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function H2(e){return Math.floor(e/2)}var G2=class{constructor(t,n){this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=n}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(H2(t),t);)this.exchange(t,H2(t)),t=H2(t)}sink(t){for(;2*t<=this.numberOfElements;){let 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_=this.transformRawCoords(b,p,l,d),x=this.getBoxForHandLandmarks(_);this.storedBoxes[i]=x;let N={landmarks:_,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(N)}else this.storedBoxes[i]=null;y.dispose()}else{let l=k0(I0(o),e4),c={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(c)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var n4=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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r4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],a4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var fr;async function pg(e){return fr||(fr=await Tt(e.body.modelPath),fr.width=parseInt(fr.signature.inputs["input_1:0"].tensorShape.dim[2].size),fr.height=parseInt(fr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Ee(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),fr}async function fg(e,t){if(!fr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=Ge.resizeBilinear(e,[fr.width,fr.height],!1),a=xe(r,[255]);r.dispose();let s;if(t.profile){let c=await qn(()=>fr.predict(a));s=c.result.find(u=>u.size===195||u.size===155).dataSync(),c.result.forEach(u=>u.dispose()),pr("blazepose",c)}else{let c=await fr.predict(a);s=c.find(u=>u.size===195||u.size===155).dataSync(),c.forEach(u=>u.dispose())}a.dispose();let i=[],o=s.length===195?r4:a4,l=5;for(let 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0.3)":oe.color,n.fill())}}}}}var ns=[];async function S4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round";for(let r=0;r<t.length;r++){if(!ns[r]&&oe.bufferedOutput&&(ns[r]={...t[r]}),n.strokeStyle=oe.color,n.lineWidth=oe.lineWidth,oe.drawPoints)for(let a=0;a<t[r].keypoints.length;a++)n.fillStyle=oe.useDepth&&t[r].keypoints[a].position.z?`rgba(${127.5+2*t[r].keypoints[a].position.z}, ${127.5-2*t[r].keypoints[a].position.z}, 255, 0.5)`:oe.color,oe.bufferedOutput?(ns[r].keypoints[a][0]=(ns[r].keypoints[a][0]+t[r].keypoints[a].position.x)/2,ns[r].keypoints[a][1]=(ns[r].keypoints[a][1]+t[r].keypoints[a].position.y)/2,E0(n,ns[r].keypoints[a][0],ns[r].keypoints[a][1])):E0(n,t[r].keypoints[a].position.x,t[r].keypoints[a].position.y);if(oe.drawLabels){n.font=oe.font;for(let a of t[r].keypoints)n.fillStyle=oe.useDepth&&a.position.z?`rgba(${127.5+2*a.position.z}, ${127.5-2*a.position.z}, 255, 0.5)`:oe.color,n.fillText(`${a.part}`,a.position.x+4,a.position.y+4)}if(oe.drawPolygons){let a,s=[];s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),s.length===5&&kg(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftKnee"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftAnkle"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHeel"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftFoot"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),R0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightKnee"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightAnkle"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHeel"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightFoot"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),R0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftElbow"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftWrist"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftPalm"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),R0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightElbow"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightWrist"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightPalm"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),R0(n,s)}}}}async function T4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=oe.font;for(let r of t){if(oe.drawBoxes&&(n.strokeStyle=oe.color,n.fillStyle=oe.color,vg(n,r.box[0],r.box[1],r.box[2],r.box[3]),oe.drawLabels&&(oe.shadowColor&&oe.shadowColor!==""&&(n.fillStyle=oe.shadowColor,n.fillText("hand",r.box[0]+3,1+r.box[1]+oe.lineHeight,r.box[2])),n.fillStyle=oe.labelColor,n.fillText("hand",r.box[0]+2,0+r.box[1]+oe.lineHeight,r.box[2])),n.stroke()),oe.drawPoints&&r.landmarks&&r.landmarks.length>0)for(let a of r.landmarks)n.fillStyle=oe.useDepth?`rgba(${127.5+2*a[2]}, ${127.5-2*a[2]}, 255, 0.5)`:oe.color,E0(n,a[0],a[1]);if(oe.drawPolygons){let a=s=>{if(!!s)for(let i=0;i<s.length;i++)n.lineWidth=oe.lineWidth,n.beginPath(),n.strokeStyle=oe.useDepth?`rgba(${127.5+2*s[i][2]}, ${127.5-2*s[i][2]}, 255, 0.5)`:oe.color,n.moveTo(s[i>0?i-1:0][0],s[i>0?i-1:0][1]),n.lineTo(s[i][0],s[i][1]),n.stroke()};a(r.annotations.indexFinger),a(r.annotations.middleFinger),a(r.annotations.ringFinger),a(r.annotations.pinky),a(r.annotations.thumb)}}}}async function C4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=oe.font;for(let r of t)if(oe.drawBoxes){if(n.strokeStyle=oe.color,n.fillStyle=oe.color,vg(n,r.box[0],r.box[1],r.box[2]-r.box[0],r.box[3]-r.box[1]),oe.drawLabels){let a=`${Math.round(100*r.score)}% ${r.label}`;oe.shadowColor&&oe.shadowColor!==""&&(n.fillStyle=oe.shadowColor,n.fillText(a,r.box[0]+3,1+r.box[1]+oe.lineHeight,r.box[2])),n.fillStyle=oe.labelColor,n.fillText(a,r.box[0]+2,0+r.box[1]+oe.lineHeight,r.box[2])}n.stroke()}}}async function dse(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function pse(e,t){!t||!e||e instanceof HTMLCanvasElement&&(I4(e,t.face),S4(e,t.body),T4(e,t.hand),N4(e,t.gesture),C4(e,t.object))}var ot=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Vc(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,r)=>(Object.keys(r||{}).forEach(a=>{let s=n[a],i=r[a];Array.isArray(s)&&Array.isArray(i)?n[a]=s.concat(...i):t(s)&&t(i)?n[a]=Vc(s,i):n[a]=i}),n),{})}var F0,Ve,Kl,Uc,jc,Di,Rt,M0,Hc,$0,Gc,D0,O0,z0,E4=class{constructor(t={}){F0.set(this,void 0);Ve.set(this,void 0);Kl.set(this,void 0);Uc.set(this,void 0);jc.set(this,void 0);Di.set(this,void 0);Rt.set(this,(...t)=>{if(!me(this,Uc))return;let n=this.tf.engine().state.numTensors,r=me(this,Kl);ta(this,Kl,n);let a=n-r;a!==0&&Ee(...t,a)});M0.set(this,t=>{if(!me(this,jc))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof je))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Hc.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=ot();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.config.debug&&Ee("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Ee("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Ee(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Ee("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&g6();try{await this.tf.setBackend(this.config.backend)}catch(r){Ee("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(Ee("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Ee(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),me(this,Ve).backend=Math.trunc(ot()-n)}});$0.set(this,t=>{if(!t||t.length<300)return{roll:null,yaw:null,pitch:null};let n=(s,i,o,l)=>Math.atan2(l-i,o-s),r=s=>Math.abs(s*180/Math.PI%360);return{roll:n(t[33][0],t[33][1],t[263][0],t[263][1]),yaw:n(t[33][0],t[33][2],t[263][0],t[263][2]),pitch:n(t[10][1],t[10][2],t[152][1],t[152][2])}});Gc.set(this,async t=>{var u,c,h,d,p,f,m;let n,r,a,s,i,o=[];this.state="run:face",n=ot();let l=await((u=this.models.face)==null?void 0:u.estimateFaces(t,this.config));if(me(this,Ve).face=Math.trunc(ot()-n),!l)return[];for(let A of l){if(me(this,Rt).call(this,"Get Face"),!A.image||A.image.isDisposedInternal){Ee("Face object is disposed:",A.image);continue}let y=me(this,$0).call(this,A.mesh);me(this,Rt).call(this,"Start Age:"),this.config.async?r=this.config.face.age.enabled?T2(A.image,this.config):{}:(this.state="run:age",n=ot(),r=this.config.face.age.enabled?await T2(A.image,this.config):{},me(this,Ve).age=Math.trunc(ot()-n)),me(this,Rt).call(this,"Start Gender:"),this.config.async?a=this.config.face.gender.enabled?$2(A.image,this.config):{}:(this.state="run:gender",n=ot(),a=this.config.face.gender.enabled?await $2(A.image,this.config):{},me(this,Ve).gender=Math.trunc(ot()-n)),me(this,Rt).call(this,"Start Emotion:"),this.config.async?s=this.config.face.emotion.enabled?L2(A.image,this.config):{}:(this.state="run:emotion",n=ot(),s=this.config.face.emotion.enabled?await L2(A.image,this.config):{},me(this,Ve).emotion=Math.trunc(ot()-n)),me(this,Rt).call(this,"End Emotion:"),me(this,Rt).call(this,"Start Embedding:"),this.config.async?i=this.config.face.embedding.enabled?U2(A,this.config):[]:(this.state="run:embedding",n=ot(),i=this.config.face.embedding.enabled?await U2(A,this.config):[],me(this,Ve).embedding=Math.trunc(ot()-n)),me(this,Rt).call(this,"End Emotion:"),this.config.async&&([r,a,s,i]=await Promise.all([r,a,s,i])),me(this,Rt).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((c=A==null?void 0:A.annotations)==null?void 0:c.leftEyeIris)&&((h=A==null?void 0:A.annotations)==null?void 0:h.rightEyeIris)&&(delete A.annotations.leftEyeIris,delete A.annotations.rightEyeIris);let g=((d=A.annotations)==null?void 0:d.leftEyeIris)&&((p=A.annotations)==null?void 0:p.rightEyeIris)?11.7*Math.max(Math.abs(A.annotations.leftEyeIris[3][0]-A.annotations.leftEyeIris[1][0]),Math.abs(A.annotations.rightEyeIris[4][1]-A.annotations.rightEyeIris[2][1])):0;o.push({...A,age:r.age,gender:a.gender,genderConfidence:a.confidence,emotion:s,embedding:i,iris:g!==0?Math.trunc(g)/100:0,angle:y,tensor:this.config.face.detector.return?(f=A.image)==null?void 0:f.squeeze():null}),(m=A.image)==null||m.dispose(),me(this,Rt).call(this,"End Face")}return me(this,Rt).call(this,"End FaceMesh:"),this.config.async&&(me(this,Ve).face&&delete me(this,Ve).face,me(this,Ve).age&&delete me(this,Ve).age,me(this,Ve).gender&&delete me(this,Ve).gender,me(this,Ve).emotion&&delete me(this,Ve).emotion),o});D0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(T0);break;case"full":n=await t(C0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});O0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+T0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+C0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));z0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(T0):t(C0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=gh,this.draw=bg,ta(this,F0,wg),this.version=_g,this.config=Vc(mt,t),this.state="idle",ta(this,Kl,0),ta(this,Uc,!1),ta(this,jc,!1),ta(this,Di,!0),ta(this,Ve,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=n=>xg(n,this.config),this.classes={facemesh:Ng,age:I2,gender:C2,emotion:D2,body:this.config.body.modelPath.includes("posenet")?tg:dg,hand:lg,nanodet:mg},this.sysinfo=Wg()}profileData(){return this.config.profile?N2:{}}simmilarity(t,n){return this.config.face.embedding.enabled?B2(t,n):0}enhance(t){return V2(t)}match(t,n,r=0){return E6(t,n,r)}async load(t={}){this.state="load";let n=ot();t&&(this.config=Vc(this.config,t)),me(this,Di)&&(this.config.debug&&Ee(`version: ${this.version}`),this.config.debug&&Ee(`tfjs version: ${this.tf.version_core}`),this.config.debug&&Ee("platform:",this.sysinfo.platform),this.config.debug&&Ee("agent:",this.sysinfo.agent),await me(this,Hc).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&Ee("configuration:",this.config),this.config.debug&&Ee("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?Ng.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?S2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?M2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?P2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?W2(this.config):null),this.models.handpose||(this.config.hand.enabled?hg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?rg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?pg(this.config):null),this.models.nanodet||(this.config.object.enabled?yg(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await Ng.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await S2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await M2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await P2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await W2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await hg(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await rg(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await pg(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await yg(this.config))),me(this,Di)&&(this.config.debug&&Ee("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),ta(this,Di,!1));let r=Math.trunc(ot()-n);r>(me(this,Ve).load||0)&&(me(this,Ve).load=r)}async detect(t,n={}){return new Promise(async r=>{var p,f,m,A;this.state="config";let a;this.config=Vc(this.config,n),this.state="check";let s=me(this,M0).call(this,t);s&&(Ee(s,t),r({error:s}));let i=ot();await me(this,Hc).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),me(this,Rt).call(this,"Start Scope:"),a=ot();let o=xg(t,this.config);if(!o||!o.tensor){Ee("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}me(this,Ve).image=Math.trunc(ot()-a),me(this,Rt).call(this,"Get Image:");let l,u,c,h;this.config.async?(c=this.config.face.enabled?me(this,Gc).call(this,o.tensor):[],me(this,Ve).face&&delete me(this,Ve).face):(this.state="run:face",a=ot(),c=this.config.face.enabled?await me(this,Gc).call(this,o.tensor):[],me(this,Ve).face=Math.trunc(ot()-a)),me(this,Rt).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(p=this.models.posenet)==null?void 0:p.estimatePoses(o.tensor,this.config):[]:l=this.config.body.enabled?fg(o.tensor,this.config):[],me(this,Ve).body&&delete me(this,Ve).body):(this.state="run:body",a=ot(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((f=this.models.posenet)==null?void 0:f.estimatePoses(o.tensor,this.config)):[]:l=this.config.body.enabled?await fg(o.tensor,this.config):[],me(this,Ve).body=Math.trunc(ot()-a)),me(this,Rt).call(this,"End Body:"),me(this,Rt).call(this,"Start Hand:"),this.config.async?(u=this.config.hand.enabled?(m=this.models.handpose)==null?void 0:m.estimateHands(o.tensor,this.config):[],me(this,Ve).hand&&delete me(this,Ve).hand):(this.state="run:hand",a=ot(),u=this.config.hand.enabled?await((A=this.models.handpose)==null?void 0:A.estimateHands(o.tensor,this.config)):[],me(this,Ve).hand=Math.trunc(ot()-a)),me(this,Rt).call(this,"End Hand:"),me(this,Rt).call(this,"Start Object:"),this.config.async?(h=this.config.object.enabled?gg(o.tensor,this.config):[],me(this,Ve).object&&delete me(this,Ve).object):(this.state="run:object",a=ot(),h=this.config.object.enabled?await gg(o.tensor,this.config):[],me(this,Ve).object=Math.trunc(ot()-a)),me(this,Rt).call(this,"End Object:"),this.config.async&&([c,l,u,h]=await Promise.all([c,l,u,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),me(this,Rt).call(this,"End Scope:");let d=[];this.config.gesture.enabled&&(a=ot(),d=[...s4(c),...a4(l),...o4(u),...i4(c)],this.config.async?me(this,Ve).gesture&&delete me(this,Ve).gesture:me(this,Ve).gesture=Math.trunc(ot()-a)),me(this,Ve).total=Math.trunc(ot()-i),this.state="idle",r({face:c,body:l,hand:u,gesture:d,object:h,performance:me(this,Ve),canvas:o.canvas})})}async warmup(t={}){let n=ot();t&&(this.config=Vc(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await me(this,D0).call(this):typeof Image!="undefined"?a=await me(this,O0).call(this):a=await me(this,z0).call(this),this.config.videoOptimized=r;let s=ot();return this.config.debug&&Ee("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};F0=new WeakMap,Ve=new WeakMap,Kl=new WeakMap,Uc=new WeakMap,jc=new WeakMap,Di=new WeakMap,Rt=new WeakMap,M0=new WeakMap,Hc=new WeakMap,$0=new WeakMap,Gc=new WeakMap,D0=new WeakMap,O0=new WeakMap,z0=new WeakMap;export{E4 as Human,E4 as default};
+2Q==`;var wg={};tr(wg,{author:()=>y4,browser:()=>m4,bugs:()=>g4,default:()=>rse,description:()=>h4,devDependencies:()=>I4,engines:()=>b4,homepage:()=>x4,keywords:()=>k4,license:()=>w4,main:()=>p4,module:()=>f4,name:()=>c4,repository:()=>_4,scripts:()=>v4,sideEffects:()=>d4,types:()=>A4,version:()=>bg});var c4="@vladmandic/human",bg="1.1.8",h4="Human: AI-powered 3D Face Detection, Face Embedding & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition",d4=!1,p4="dist/human.node.js",f4="dist/human.esm.js",m4="dist/human.esm.js",A4="types/src/human.d.ts",y4="Vladimir Mandic <mandic00@live.com>",g4={url:"https://github.com/vladmandic/human/issues"},x4="https://vladmandic.github.io/human/demo/index.html",w4="MIT",b4={node:">=12.0.0"},_4={type:"git",url:"git+https://github.com/vladmandic/human.git"},v4={start:"node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation demo/node.js",dev:"node 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start"},k4=["tensorflowjs","face-detection","face-geometry","face-embedding","face-recognition","body-tracking","hand-tracking","iris-tracking","age-estimation","emotion-detection","gender-prediction","gesture-recognition","blazeface","blazepose","nanodet"],I4={"@microsoft/api-extractor":"^7.13.2","@tensorflow/tfjs":"^3.3.0","@tensorflow/tfjs-backend-cpu":"^3.3.0","@tensorflow/tfjs-backend-wasm":"^3.3.0","@tensorflow/tfjs-backend-webgl":"^3.3.0","@tensorflow/tfjs-converter":"^3.3.0","@tensorflow/tfjs-core":"^3.3.0","@tensorflow/tfjs-data":"^3.3.0","@tensorflow/tfjs-layers":"^3.3.0","@tensorflow/tfjs-node":"^3.3.0","@tensorflow/tfjs-node-gpu":"^3.3.0","@types/node":"^14.14.35","@typescript-eslint/eslint-plugin":"^4.18.0","@typescript-eslint/parser":"^4.18.0","@vladmandic/pilogger":"^0.2.14",chokidar:"^3.5.1",dayjs:"^1.10.4",esbuild:"^0.9.3",eslint:"^7.22.0","eslint-config-airbnb-base":"^14.2.1","eslint-plugin-import":"^2.22.1","eslint-plugin-json":"^2.1.2","eslint-plugin-node":"^11.1.0","eslint-plugin-promise":"^4.3.1",rimraf:"^3.0.2",seedrandom:"^3.0.5","simple-git":"^2.37.0",tslib:"^2.1.0",typedoc:"^0.20.32",typescript:"^4.2.3"},rse={name:c4,version:bg,description:h4,sideEffects:d4,main:p4,module:f4,browser:m4,types:A4,author:y4,bugs:g4,homepage:x4,license:w4,engines:b4,repository:_4,scripts:v4,keywords:k4,devDependencies:I4};var _g={};tr(_g,{all:()=>sse,body:()=>T4,canvas:()=>ase,drawOptions:()=>ie,face:()=>S4,gesture:()=>N4,hand:()=>C4,object:()=>E4});var ie={color:"rgba(173, 216, 230, 0.3)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",font:'small-caps 16px "Segoe UI"',lineHeight:20,lineWidth:6,pointSize:2,roundRect:28,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawPolygons:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,bufferedOutput:!1,useRawBoxes:!1};function R0(e,t,n,r=null){e.fillStyle=ie.useDepth&&r?`rgba(${127.5+2*(r||0)}, ${127.5-2*(r||0)}, 255, 0.3)`:ie.color,e.beginPath(),e.arc(t,n,ie.pointSize,0,2*Math.PI),e.fill()}function Kl(e,t,n,r,a){if(e.beginPath(),ie.useCurves){let s=(t+t+r)/2,i=(n+n+a)/2;e.ellipse(s,i,r/2,a/2,0,0,2*Math.PI)}else e.lineWidth=ie.lineWidth,e.moveTo(t+ie.roundRect,n),e.lineTo(t+r-ie.roundRect,n),e.quadraticCurveTo(t+r,n,t+r,n+ie.roundRect),e.lineTo(t+r,n+a-ie.roundRect),e.quadraticCurveTo(t+r,n+a,t+r-ie.roundRect,n+a),e.lineTo(t+ie.roundRect,n+a),e.quadraticCurveTo(t,n+a,t,n+a-ie.roundRect),e.lineTo(t,n+ie.roundRect),e.quadraticCurveTo(t,n,t+ie.roundRect,n),e.closePath();e.stroke()}function vg(e,t=[]){if(!(t===void 0||t.length===0)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=ie.useDepth&&n[2]?`rgba(${127.5+2*n[2]}, ${127.5-2*n[2]}, 255, 0.3)`:ie.color,e.fillStyle=ie.useDepth&&n[2]?`rgba(${127.5+2*n[2]}, ${127.5-2*n[2]}, 255, 0.3)`:ie.color,e.lineTo(n[0],parseInt(n[1]));e.stroke(),ie.fillPolygons&&(e.closePath(),e.fill())}}function M0(e,t=[]){if(!(t===void 0||t.length===0)){if(!ie.useCurves||t.length<=2){vg(e,t);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,a=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,a)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),ie.fillPolygons&&(e.closePath(),e.fill())}}async function N4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!n)return;n.font=ie.font,n.fillStyle=ie.color;let r=1;for(let a=0;a<t.length;a++){let s=[],i=[];if([s,i]=Object.entries(t[a]),i.length>1&&i[1].length>0){let o=s[1]>0?`#${s[1]}`:"",l=`${s[0]} ${o}: ${i[1]}`;ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText(l,8,2+r*ie.lineHeight)),n.fillStyle=ie.labelColor,n.fillText(l,6,0+r*ie.lineHeight),r+=1}}}async function S4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n)for(let r of t){n.font=ie.font,n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.drawBoxes&&(ie.useRawBoxes?Kl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Kl(n,r.box[0],r.box[1],r.box[2],r.box[3]));let a=[];if(a.push(`face confidence: ${Math.trunc(100*r.confidence)}%`),r.genderConfidence&&a.push(`${r.gender||""} ${Math.trunc(100*r.genderConfidence)}% confident`),r.age&&a.push(`age: ${r.age||""}`),r.iris&&a.push(`iris distance: ${r.iris}`),r.emotion&&r.emotion.length>0){let s=r.emotion.map(i=>`${Math.trunc(100*i.score)}% ${i.emotion}`);a.push(s.join(" "))}r.angle&&r.angle.roll&&a.push(`roll: ${Math.trunc(100*r.angle.roll)/100} yaw:${Math.trunc(100*r.angle.yaw)/100} pitch:${Math.trunc(100*r.angle.pitch)/100}`),a.length===0&&a.push("face"),n.fillStyle=ie.color;for(let s=a.length-1;s>=0;s--){let i=Math.max(r.box[0],0),o=s*ie.lineHeight+r.box[1];ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText(a[s],i+5,o+16)),n.fillStyle=ie.labelColor,n.fillText(a[s],i+4,o+15)}if(n.lineWidth=1,r.mesh&&r.mesh.length>0){if(ie.drawPoints)for(let s of r.mesh)R0(n,s[0],s[1],s[2]);if(ie.drawPolygons){n.lineWidth=1;for(let s=0;s<Fi.length/3;s++){let i=[Fi[s*3+0],Fi[s*3+1],Fi[s*3+2]].map(o=>r.mesh[o]);vg(n,i)}if(r.annotations&&r.annotations.leftEyeIris){n.strokeStyle=ie.useDepth?"rgba(255, 200, 255, 0.3)":ie.color,n.beginPath();let s=Math.abs(r.annotations.leftEyeIris[3][0]-r.annotations.leftEyeIris[1][0])/2,i=Math.abs(r.annotations.leftEyeIris[4][1]-r.annotations.leftEyeIris[2][1])/2;n.ellipse(r.annotations.leftEyeIris[0][0],r.annotations.leftEyeIris[0][1],s,i,0,0,2*Math.PI),n.stroke(),ie.fillPolygons&&(n.fillStyle=ie.useDepth?"rgba(255, 255, 200, 0.3)":ie.color,n.fill())}if(r.annotations&&r.annotations.rightEyeIris){n.strokeStyle=ie.useDepth?"rgba(255, 200, 255, 0.3)":ie.color,n.beginPath();let s=Math.abs(r.annotations.rightEyeIris[3][0]-r.annotations.rightEyeIris[1][0])/2,i=Math.abs(r.annotations.rightEyeIris[4][1]-r.annotations.rightEyeIris[2][1])/2;n.ellipse(r.annotations.rightEyeIris[0][0],r.annotations.rightEyeIris[0][1],s,i,0,0,2*Math.PI),n.stroke(),ie.fillPolygons&&(n.fillStyle=ie.useDepth?"rgba(255, 255, 200, 0.3)":ie.color,n.fill())}}}}}var ns=[];async function T4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round";for(let r=0;r<t.length;r++){if(!ns[r]&&ie.bufferedOutput&&(ns[r]={...t[r]}),n.strokeStyle=ie.color,n.lineWidth=ie.lineWidth,ie.drawPoints)for(let a=0;a<t[r].keypoints.length;a++)n.fillStyle=ie.useDepth&&t[r].keypoints[a].position.z?`rgba(${127.5+2*t[r].keypoints[a].position.z}, ${127.5-2*t[r].keypoints[a].position.z}, 255, 0.5)`:ie.color,ie.bufferedOutput?(ns[r].keypoints[a][0]=(ns[r].keypoints[a][0]+t[r].keypoints[a].position.x)/2,ns[r].keypoints[a][1]=(ns[r].keypoints[a][1]+t[r].keypoints[a].position.y)/2,R0(n,ns[r].keypoints[a][0],ns[r].keypoints[a][1])):R0(n,t[r].keypoints[a].position.x,t[r].keypoints[a].position.y);if(ie.drawLabels){n.font=ie.font;for(let a of t[r].keypoints)n.fillStyle=ie.useDepth&&a.position.z?`rgba(${127.5+2*a.position.z}, ${127.5-2*a.position.z}, 255, 0.5)`:ie.color,n.fillText(`${a.part}`,a.position.x+4,a.position.y+4)}if(ie.drawPolygons){let a,s=[];s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),s.length===5&&vg(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftKnee"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftAnkle"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHeel"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftFoot"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),M0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightKnee"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightAnkle"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHeel"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightFoot"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),M0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftElbow"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftWrist"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftPalm"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),M0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightElbow"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightWrist"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightPalm"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),M0(n,s)}}}}async function C4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=ie.font;for(let r of t){if(ie.drawBoxes&&(n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.useRawBoxes?Kl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Kl(n,r.box[0],r.box[1],r.box[2],r.box[3]),ie.drawLabels&&(ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText("hand",r.box[0]+3,1+r.box[1]+ie.lineHeight,r.box[2])),n.fillStyle=ie.labelColor,n.fillText("hand",r.box[0]+2,0+r.box[1]+ie.lineHeight,r.box[2])),n.stroke()),ie.drawPoints&&r.landmarks&&r.landmarks.length>0)for(let a of r.landmarks)n.fillStyle=ie.useDepth?`rgba(${127.5+2*a[2]}, ${127.5-2*a[2]}, 255, 0.5)`:ie.color,R0(n,a[0],a[1]);if(ie.drawPolygons){let a=s=>{if(!!s)for(let i=0;i<s.length;i++)n.lineWidth=ie.lineWidth,n.beginPath(),n.strokeStyle=ie.useDepth?`rgba(${127.5+2*s[i][2]}, ${127.5-2*s[i][2]}, 255, 0.5)`:ie.color,n.moveTo(s[i>0?i-1:0][0],s[i>0?i-1:0][1]),n.lineTo(s[i][0],s[i][1]),n.stroke()};a(r.annotations.indexFinger),a(r.annotations.middleFinger),a(r.annotations.ringFinger),a(r.annotations.pinky),a(r.annotations.thumb)}}}}async function E4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=ie.font;for(let r of t)if(ie.drawBoxes){if(n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.useRawBoxes?Kl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Kl(n,r.box[0],r.box[1],r.box[2],r.box[3]),ie.drawLabels){let a=`${Math.round(100*r.score)}% ${r.label}`;ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText(a,r.box[0]+3,1+r.box[1]+ie.lineHeight,r.box[2])),n.fillStyle=ie.labelColor,n.fillText(a,r.box[0]+2,0+r.box[1]+ie.lineHeight,r.box[2])}n.stroke()}}}async function ase(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function sse(e,t){!t||!e||e instanceof HTMLCanvasElement&&(S4(e,t.face),T4(e,t.body),C4(e,t.hand),N4(e,t.gesture),E4(e,t.object))}var it=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Uc(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,r)=>(Object.keys(r||{}).forEach(a=>{let s=n[a],i=r[a];Array.isArray(s)&&Array.isArray(i)?n[a]=s.concat(...i):t(s)&&t(i)?n[a]=Uc(s,i):n[a]=i}),n),{})}var F0,Ve,Zl,jc,Hc,Di,Rt,$0,Gc,D0,qc,O0,z0,P0,R4=class{constructor(t={}){F0.set(this,void 0);Ve.set(this,void 0);Zl.set(this,void 0);jc.set(this,void 0);Hc.set(this,void 0);Di.set(this,void 0);Rt.set(this,(...t)=>{if(!me(this,jc))return;let n=this.tf.engine().state.numTensors,r=me(this,Zl);ta(this,Zl,n);let a=n-r;a!==0&&Ee(...t,a)});$0.set(this,t=>{if(!me(this,Hc))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof je))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Gc.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=it();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.config.debug&&Ee("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Ee("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Ee(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Ee("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&x6();try{await this.tf.setBackend(this.config.backend)}catch(r){Ee("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(Ee("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Ee(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),me(this,Ve).backend=Math.trunc(it()-n)}});D0.set(this,t=>{if(!t||t.length<300)return{roll:null,yaw:null,pitch:null};let n=(s,i,o,l)=>Math.atan2(l-i,o-s),r=s=>Math.abs(s*180/Math.PI%360);return{roll:n(t[33][0],t[33][1],t[263][0],t[263][1]),yaw:n(t[33][0],t[33][2],t[263][0],t[263][2]),pitch:n(t[10][1],t[10][2],t[152][1],t[152][2])}});qc.set(this,async t=>{var c,u,h,d,p,f,m;let n,r,a,s,i,o=[];this.state="run:face",n=it();let l=await((c=this.models.face)==null?void 0:c.estimateFaces(t,this.config));if(me(this,Ve).face=Math.trunc(it()-n),!l)return[];for(let A of l){if(me(this,Rt).call(this,"Get Face"),!A.image||A.image.isDisposedInternal){Ee("Face object is disposed:",A.image);continue}let y=me(this,D0).call(this,A.mesh);me(this,Rt).call(this,"Start Age:"),this.config.async?r=this.config.face.age.enabled?T2(A.image,this.config):{}:(this.state="run:age",n=it(),r=this.config.face.age.enabled?await T2(A.image,this.config):{},me(this,Ve).age=Math.trunc(it()-n)),me(this,Rt).call(this,"Start Gender:"),this.config.async?a=this.config.face.gender.enabled?$2(A.image,this.config):{}:(this.state="run:gender",n=it(),a=this.config.face.gender.enabled?await $2(A.image,this.config):{},me(this,Ve).gender=Math.trunc(it()-n)),me(this,Rt).call(this,"Start Emotion:"),this.config.async?s=this.config.face.emotion.enabled?L2(A.image,this.config):{}:(this.state="run:emotion",n=it(),s=this.config.face.emotion.enabled?await L2(A.image,this.config):{},me(this,Ve).emotion=Math.trunc(it()-n)),me(this,Rt).call(this,"End Emotion:"),me(this,Rt).call(this,"Start Embedding:"),this.config.async?i=this.config.face.embedding.enabled?U2(A,this.config):[]:(this.state="run:embedding",n=it(),i=this.config.face.embedding.enabled?await U2(A,this.config):[],me(this,Ve).embedding=Math.trunc(it()-n)),me(this,Rt).call(this,"End Emotion:"),this.config.async&&([r,a,s,i]=await Promise.all([r,a,s,i])),me(this,Rt).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((u=A==null?void 0:A.annotations)==null?void 0:u.leftEyeIris)&&((h=A==null?void 0:A.annotations)==null?void 0:h.rightEyeIris)&&(delete A.annotations.leftEyeIris,delete A.annotations.rightEyeIris);let g=((d=A.annotations)==null?void 0:d.leftEyeIris)&&((p=A.annotations)==null?void 0:p.rightEyeIris)?11.7*Math.max(Math.abs(A.annotations.leftEyeIris[3][0]-A.annotations.leftEyeIris[1][0]),Math.abs(A.annotations.rightEyeIris[4][1]-A.annotations.rightEyeIris[2][1])):0;o.push({...A,age:r.age,gender:a.gender,genderConfidence:a.confidence,emotion:s,embedding:i,iris:g!==0?Math.trunc(g)/100:0,angle:y,tensor:this.config.face.detector.return?(f=A.image)==null?void 0:f.squeeze():null}),(m=A.image)==null||m.dispose(),me(this,Rt).call(this,"End Face")}return me(this,Rt).call(this,"End FaceMesh:"),this.config.async&&(me(this,Ve).face&&delete me(this,Ve).face,me(this,Ve).age&&delete me(this,Ve).age,me(this,Ve).gender&&delete me(this,Ve).gender,me(this,Ve).emotion&&delete me(this,Ve).emotion),o});O0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(C0);break;case"full":n=await t(E0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});z0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+C0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+E0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));P0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(C0):t(E0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=xh,this.draw=_g,ta(this,F0,wg),this.version=bg,this.config=Uc(ft,t),this.state="idle",ta(this,Zl,0),ta(this,jc,!1),ta(this,Hc,!1),ta(this,Di,!0),ta(this,Ve,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=n=>xg(n,this.config),this.classes={facemesh:kg,age:N2,gender:C2,emotion:D2,body:this.config.body.modelPath.includes("posenet")?tg:dg,hand:lg,nanodet:mg},this.sysinfo=Lg()}profileData(){return this.config.profile?I2:{}}simmilarity(t,n){return this.config.face.embedding.enabled?B2(t,n):0}enhance(t){return V2(t)}match(t,n,r=0){return R6(t,n,r)}async load(t={}){this.state="load";let n=it();t&&(this.config=Uc(this.config,t)),me(this,Di)&&(this.config.debug&&Ee(`version: ${this.version}`),this.config.debug&&Ee(`tfjs version: ${this.tf.version_core}`),this.config.debug&&Ee("platform:",this.sysinfo.platform),this.config.debug&&Ee("agent:",this.sysinfo.agent),await me(this,Gc).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&Ee("configuration:",this.config),this.config.debug&&Ee("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?kg.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?S2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?F2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?P2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?W2(this.config):null),this.models.handpose||(this.config.hand.enabled?hg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?rg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?pg(this.config):null),this.models.nanodet||(this.config.object.enabled?yg(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await kg.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await S2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await F2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await P2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await W2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await hg(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await rg(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await pg(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await yg(this.config))),me(this,Di)&&(this.config.debug&&Ee("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),ta(this,Di,!1));let r=Math.trunc(it()-n);r>(me(this,Ve).load||0)&&(me(this,Ve).load=r)}async detect(t,n={}){return new Promise(async r=>{var f,m,A,y;this.state="config";let a;this.config=Uc(this.config,n),this.state="check";let s=me(this,$0).call(this,t);s&&(Ee(s,t),r({error:s}));let i=it();await me(this,Gc).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),me(this,Rt).call(this,"Start Scope:"),a=it();let o=xg(t,this.config);if(!o||!o.tensor){Ee("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}me(this,Ve).image=Math.trunc(it()-a),me(this,Rt).call(this,"Get Image:");let l,c,u,h;this.config.async?(u=this.config.face.enabled?me(this,qc).call(this,o.tensor):[],me(this,Ve).face&&delete me(this,Ve).face):(this.state="run:face",a=it(),u=this.config.face.enabled?await me(this,qc).call(this,o.tensor):[],me(this,Ve).face=Math.trunc(it()-a)),me(this,Rt).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(f=this.models.posenet)==null?void 0:f.estimatePoses(o.tensor,this.config):[]:l=this.config.body.enabled?fg(o.tensor,this.config):[],me(this,Ve).body&&delete me(this,Ve).body):(this.state="run:body",a=it(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((m=this.models.posenet)==null?void 0:m.estimatePoses(o.tensor,this.config)):[]:l=this.config.body.enabled?await fg(o.tensor,this.config):[],me(this,Ve).body=Math.trunc(it()-a)),me(this,Rt).call(this,"End Body:"),me(this,Rt).call(this,"Start Hand:"),this.config.async?(c=this.config.hand.enabled?(A=this.models.handpose)==null?void 0:A.estimateHands(o.tensor,this.config):[],me(this,Ve).hand&&delete me(this,Ve).hand):(this.state="run:hand",a=it(),c=this.config.hand.enabled?await((y=this.models.handpose)==null?void 0:y.estimateHands(o.tensor,this.config)):[],me(this,Ve).hand=Math.trunc(it()-a)),me(this,Rt).call(this,"End Hand:"),me(this,Rt).call(this,"Start Object:"),this.config.async?(h=this.config.object.enabled?gg(o.tensor,this.config):[],me(this,Ve).object&&delete me(this,Ve).object):(this.state="run:object",a=it(),h=this.config.object.enabled?await gg(o.tensor,this.config):[],me(this,Ve).object=Math.trunc(it()-a)),me(this,Rt).call(this,"End Object:"),this.config.async&&([u,l,c,h]=await Promise.all([u,l,c,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),me(this,Rt).call(this,"End Scope:");let d=[];this.config.gesture.enabled&&(a=it(),d=[...i4(u),...s4(l),...l4(c),...o4(u)],this.config.async?me(this,Ve).gesture&&delete me(this,Ve).gesture:me(this,Ve).gesture=Math.trunc(it()-a)),me(this,Ve).total=Math.trunc(it()-i),this.state="idle";let p={face:u,body:l,hand:c,gesture:d,object:h,performance:me(this,Ve),canvas:o.canvas};r(p)})}async warmup(t={}){let n=it();t&&(this.config=Uc(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await me(this,O0).call(this):typeof Image!="undefined"?a=await me(this,z0).call(this):a=await me(this,P0).call(this),this.config.videoOptimized=r;let s=it();return this.config.debug&&Ee("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};F0=new WeakMap,Ve=new WeakMap,Zl=new WeakMap,jc=new WeakMap,Hc=new WeakMap,Di=new WeakMap,Rt=new WeakMap,$0=new WeakMap,Gc=new WeakMap,D0=new WeakMap,qc=new WeakMap,O0=new WeakMap,z0=new WeakMap,P0=new WeakMap;export{R4 as Human,R4 as default};
 /**
  * @license
  * Copyright 2017 Google LLC. All Rights Reserved.
diff --git a/dist/human.esm.js.map b/dist/human.esm.js.map
index 947095ec..66d84a04 100644
--- a/dist/human.esm.js.map
+++ b/dist/human.esm.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
-  "sources": ["../src/blazeface/facemesh.ts", "../src/posenet/keypoints.ts", "../src/log.ts", "../src/sysinfo.ts", "../node_modules/node-fetch/browser.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/alea.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xor128.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xorwow.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xorshift7.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xor4096.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/tychei.js", "(disabled):crypto", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/seedrandom.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/index.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/alea.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xor128.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xorwow.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xorshift7.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xor4096.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/tychei.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/seedrandom.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/index.js", "(disabled):path", "(disabled):worker_threads", "(disabled):perf_hooks", "../node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js", "../node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js", "../node_modules/seedrandom/lib/alea.js", "../node_modules/seedrandom/lib/xor128.js", "../node_modules/seedrandom/lib/xorwow.js", "../node_modules/seedrandom/lib/xorshift7.js", "../node_modules/seedrandom/lib/xor4096.js", "../node_modules/seedrandom/lib/tychei.js", "../node_modules/seedrandom/seedrandom.js", "../node_modules/seedrandom/index.js", "../node_modules/string_decoder/lib/string_decoder.js", "../node_modules/@tensorflow/tfjs-core/src/backends/backend.ts", "../node_modules/@tensorflow/tfjs-core/src/util_base.ts", "../node_modules/@tensorflow/tfjs-core/src/environment.ts", "../node_modules/@tensorflow/tfjs-core/src/global_util.ts", "../node_modules/@tensorflow/tfjs-core/src/kernel_names.ts", "../node_modules/@tensorflow/tfjs-core/src/kernel_registry.ts", "../node_modules/@tensorflow/tfjs-core/src/util.ts", "../node_modules/@tensorflow/tfjs-core/src/profiler.ts", "../node_modules/@tensorflow/tfjs-core/src/tape.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor_format.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor_util.ts", "../node_modules/@tensorflow/tfjs-core/src/types.ts", "../node_modules/@tensorflow/tfjs-core/src/engine.ts", "../node_modules/@tensorflow/tfjs-core/src/device_util.ts", "../node_modules/@tensorflow/tfjs-core/src/flags.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor_util_env.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/operation.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/complex.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/tensor_ops_util.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/tensor.ts", "../node_modules/@tensorflow/tfjs-core/src/io/types.ts", "../node_modules/@tensorflow/tfjs-core/src/io/io_utils.ts", "../node_modules/@tensorflow/tfjs-core/src/io/router_registry.ts", "../node_modules/@tensorflow/tfjs-core/src/io/indexed_db.ts", "../node_modules/@tensorflow/tfjs-core/src/io/local_storage.ts", "../node_modules/@tensorflow/tfjs-core/src/io/model_management.ts", "../node_modules/@tensorflow/tfjs-core/src/platforms/platform_browser.ts", "../node_modules/@tensorflow/tfjs-core/src/platforms/platform_node.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/buffer.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/cast.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/clone.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/print.ts", "../node_modules/@tensorflow/tfjs-core/src/base_side_effects.ts", "../node_modules/@tensorflow/tfjs-core/src/io/io.ts", "../node_modules/@tensorflow/tfjs-core/src/io/browser_files.ts", "../node_modules/@tensorflow/tfjs-core/src/io/progress.ts", "../node_modules/@tensorflow/tfjs-core/src/io/weights_loader.ts", "../node_modules/@tensorflow/tfjs-core/src/io/http.ts", "../node_modules/@tensorflow/tfjs-core/src/io/passthrough.ts", "../node_modules/@tensorflow/tfjs-core/src/math.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/mat_mul.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/one_hot.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/transpose.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/confusion_matrix.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/browser.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/tensor3d.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/gather_nd_util.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/scatter_nd_util.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/slice_util.ts", "../node_modules/@tensorflow/tfjs-core/src/serialization.ts", "../node_modules/@tensorflow/tfjs-core/src/test_util.ts", "../node_modules/@tensorflow/tfjs-core/src/version.ts", "../node_modules/@tensorflow/tfjs-core/src/globals.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/add.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/floorDiv.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/div.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/mul.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/abs.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/acos.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/acosh.ts", 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"../node_modules/@tensorflow/tfjs-data/src/iterators/byte_chunk_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/file_chunk_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/url_chunk_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/util/source_util.ts", "../node_modules/@tensorflow/tfjs-data/src/sources/file_data_source.ts", "../node_modules/@tensorflow/tfjs-data/src/sources/url_data_source.ts", "../node_modules/@tensorflow/tfjs-data/src/readers.ts", "../node_modules/@tensorflow/tfjs-data/src/version.ts", "../src/tfjs/tf-browser.ts", "../src/tfjs/backend.ts", "../src/blazeface/blazeface.ts", "../src/blazeface/box.ts", "../src/blazeface/util.ts", "../src/blazeface/coords.ts", "../src/blazeface/facepipeline.ts", "../src/human.ts", "../src/age/age.ts", "../src/profile.ts", "../src/gender/gender.ts", "../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/decodePose.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/box.ts", "../src/handpose/handdetector.ts", "../src/handpose/util.ts", "../src/handpose/handpipeline.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/nanodet/nanodet.ts", "../src/gesture/gesture.ts", "../src/imagefx.js", "../src/image.ts", "../config.ts", "../src/sample.ts", "../src/draw.ts"],
-  "sourcesContent": ["import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - prediction.box.startPoint[0],\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - prediction.box.startPoint[1],\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0] / input.shape[2]),\n        Math.max(0, prediction.box.startPoint[1] / input.shape[1]),\n        Math.min(input.shape[1], (prediction.box.endPoint[0]) - prediction.box.startPoint[0]) / input.shape[2],\n        Math.min(input.shape[2], (prediction.box.endPoint[1]) - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        mesh,\n        boxRaw,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModuleThreadedSimd) {\n  WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};\n\nfunction GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP32}function GROWABLE_HEAP_U32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!==\"undefined\"?WasmBackendModuleThreadedSimd:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var ENVIRONMENT_IS_PTHREAD=Module[\"ENVIRONMENT_IS_PTHREAD\"]||false;if(ENVIRONMENT_IS_PTHREAD){buffer=Module[\"buffer\"]}var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"};var nodeWorkerThreads;try{nodeWorkerThreads=require(\"worker_threads\")}catch(e){console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}global.Worker=nodeWorkerThreads.Worker}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(typeof _scriptDir !== \"undefined\" && _scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}if(ENVIRONMENT_IS_NODE){read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret}}else{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}if(ENVIRONMENT_IS_NODE){if(typeof performance===\"undefined\"){global.performance=require(\"perf_hooks\").performance}}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var Atomics_load=Atomics.load;var Atomics_store=Atomics.store;var Atomics_compareExchange=Atomics.compareExchange;var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function 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the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];var contextAttributes={\"alpha\":!!GROWABLE_HEAP_I32()[a+(0>>2)],\"depth\":!!GROWABLE_HEAP_I32()[a+(4>>2)],\"stencil\":!!GROWABLE_HEAP_I32()[a+(8>>2)],\"antialias\":!!GROWABLE_HEAP_I32()[a+(12>>2)],\"premultipliedAlpha\":!!GROWABLE_HEAP_I32()[a+(16>>2)],\"preserveDrawingBuffer\":!!GROWABLE_HEAP_I32()[a+(20>>2)],\"powerPreference\":__emscripten_webgl_power_preferences[powerPreference],\"failIfMajorPerformanceCaveat\":!!GROWABLE_HEAP_I32()[a+(28>>2)],majorVersion:GROWABLE_HEAP_I32()[a+(32>>2)],minorVersion:GROWABLE_HEAP_I32()[a+(36>>2)],enableExtensionsByDefault:GROWABLE_HEAP_I32()[a+(40>>2)],explicitSwapControl:GROWABLE_HEAP_I32()[a+(44>>2)],proxyContextToMainThread:GROWABLE_HEAP_I32()[a+(48>>2)],renderViaOffscreenBackBuffer:GROWABLE_HEAP_I32()[a+(52>>2)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"ba\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"ca\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"da\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"ea\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"fa\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"ga\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"ha\"]).apply(null,arguments)};var 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_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=function(){return(_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=Module[\"asm\"][\"gb\"]).apply(null,arguments)};var __emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=function(){return(__emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=Module[\"asm\"][\"hb\"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=function(){return(_emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=Module[\"asm\"][\"ib\"]).apply(null,arguments)};var _emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=function(){return(_emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=Module[\"asm\"][\"jb\"]).apply(null,arguments)};var __emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=function(){return(__emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=Module[\"asm\"][\"kb\"]).apply(null,arguments)};var _emscripten_tls_init=Module[\"_emscripten_tls_init\"]=function(){return(_emscripten_tls_init=Module[\"_emscripten_tls_init\"]=Module[\"asm\"][\"lb\"]).apply(null,arguments)};var __emscripten_thread_init=Module[\"__emscripten_thread_init\"]=function(){return(__emscripten_thread_init=Module[\"__emscripten_thread_init\"]=Module[\"asm\"][\"mb\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"nb\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"ob\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"pb\"]).apply(null,arguments)};var _emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=function(){return(_emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=Module[\"asm\"][\"qb\"]).apply(null,arguments)};var _memalign=Module[\"_memalign\"]=function(){return(_memalign=Module[\"_memalign\"]=Module[\"asm\"][\"rb\"]).apply(null,arguments)};var __emscripten_allow_main_runtime_queued_calls=Module[\"__emscripten_allow_main_runtime_queued_calls\"]=9880;var __emscripten_main_thread_futex=Module[\"__emscripten_main_thread_futex\"]=11368;Module[\"cwrap\"]=cwrap;Module[\"PThread\"]=PThread;Module[\"PThread\"]=PThread;Module[\"wasmMemory\"]=wasmMemory;Module[\"ExitStatus\"]=ExitStatus;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}if(ENVIRONMENT_IS_PTHREAD){readyPromiseResolve(Module);postMessage({\"cmd\":\"loaded\"});return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;function exit(status,implicit){if(implicit&&noExitRuntime&&status===0){return}if(!implicit){if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exitProcess\",\"returnCode\":status});throw new ExitStatus(status)}else{}}if(noExitRuntime){}else{PThread.terminateAllThreads();EXITSTATUS=status;exitRuntime();if(Module[\"onExit\"])Module[\"onExit\"](status);ABORT=true}quit_(status,new ExitStatus(status))}if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}if(ENVIRONMENT_IS_PTHREAD){noExitRuntime=false;PThread.initWorker()}run();\n\n\n  return WasmBackendModuleThreadedSimd.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModuleThreadedSimd;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModuleThreadedSimd; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd;\n", "\nvar WasmBackendModule = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModule) {\n  WasmBackendModule = WasmBackendModule || {};\n\nvar Module=typeof WasmBackendModule!==\"undefined\"?WasmBackendModule:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var 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XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return 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Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(e){try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 0.694710969924927],\n  [0.392388999462128, 0.694203019142151],\n  [0.277076005935669, 0.271932005882263],\n  [0.422551989555359, 0.563233017921448],\n  [0.385919004678726, 0.281364023685455],\n  [0.383103013038635, 0.255840003490448],\n  [0.331431001424789, 0.119714021682739],\n  [0.229923993349075, 0.232002973556519],\n  [0.364500999450684, 0.189113974571228],\n  [0.229622006416321, 0.299540996551514],\n  [0.173287004232407, 0.278747975826263],\n  [0.472878992557526, 0.666198015213013],\n  [0.446828007698059, 0.668527007102966],\n  [0.422762006521225, 0.673889994621277],\n  [0.445307999849319, 0.580065965652466],\n  [0.388103008270264, 0.693961024284363],\n  [0.403039008378983, 0.706539988517761],\n  [0.403629004955292, 0.693953037261963],\n  [0.460041999816895, 0.557139039039612],\n  [0.431158006191254, 0.692366003990173],\n  [0.452181994915009, 0.692366003990173],\n  [0.475387006998062, 0.692366003990173],\n  [0.465828001499176, 0.779190003871918],\n  [0.472328990697861, 0.736225962638855],\n  [0.473087012767792, 0.717857003211975],\n  [0.473122000694275, 0.704625964164734],\n  [0.473033010959625, 0.695277988910675],\n  [0.427942007780075, 0.695277988910675],\n  [0.426479011774063, 0.703539967536926],\n  [0.423162013292313, 0.711845993995667],\n  [0.4183090031147, 0.720062971115112],\n  [0.390094995498657, 0.639572978019714],\n  [0.013953999616206, 0.560034036636353],\n  [0.499913990497589, 0.58014702796936],\n  [0.413199990987778, 0.69539999961853],\n  [0.409626007080078, 0.701822996139526],\n  [0.468080013990402, 0.601534962654114],\n  [0.422728985548019, 0.585985004901886],\n  [0.463079988956451, 0.593783974647522],\n  [0.37211999297142, 0.47341400384903],\n  [0.334562003612518, 0.496073007583618],\n  [0.411671012639999, 0.546965003013611],\n  [0.242175996303558, 0.14767599105835],\n  [0.290776997804642, 0.201445996761322],\n  [0.327338010072708, 0.256527006626129],\n  [0.399509996175766, 0.748921036720276],\n  [0.441727995872498, 0.261676013469696],\n  [0.429764986038208, 0.187834024429321],\n  [0.412198007106781, 0.108901023864746],\n  [0.288955003023148, 0.398952007293701],\n  [0.218936994671822, 0.435410976409912],\n  [0.41278201341629, 0.398970007896423],\n  [0.257135003805161, 0.355440020561218],\n  [0.427684992551804, 0.437960982322693],\n  [0.448339998722076, 0.536936044692993],\n  [0.178560003638268, 0.45755398273468],\n  [0.247308000922203, 0.457193970680237],\n  [0.286267012357712, 0.467674970626831],\n  [0.332827985286713, 0.460712015628815],\n  [0.368755996227264, 0.447206974029541],\n  [0.398963987827301, 0.432654976844788],\n  [0.476410001516342, 0.405806005001068],\n  [0.189241006970406, 0.523923993110657],\n  [0.228962004184723, 0.348950982093811],\n  [0.490725994110107, 0.562400996685028],\n  [0.404670000076294, 0.485132992267609],\n  [0.019469000399113, 0.401564002037048],\n  [0.426243007183075, 0.420431017875671],\n  [0.396993011236191, 0.548797011375427],\n  [0.266469985246658, 0.376977026462555],\n  [0.439121007919312, 0.51895797252655],\n  [0.032313998788595, 0.644356966018677],\n  [0.419054001569748, 0.387154996395111],\n  [0.462783008813858, 0.505746960639954],\n  [0.238978996872902, 0.779744982719421],\n  [0.198220998048782, 0.831938028335571],\n  [0.107550002634525, 0.540755033493042],\n  [0.183610007166862, 0.740257024765015],\n  [0.134409993886948, 0.333683013916016],\n  [0.385764002799988, 0.883153975009918],\n  [0.490967005491257, 0.579378008842468],\n  [0.382384985685349, 0.508572995662689],\n  [0.174399003386497, 0.397670984268188],\n  [0.318785011768341, 0.39623498916626],\n  [0.343364000320435, 0.400596976280212],\n  [0.396100014448166, 0.710216999053955],\n  [0.187885001301765, 0.588537991046906],\n  [0.430987000465393, 0.944064974784851],\n  [0.318993002176285, 0.898285031318665],\n  [0.266247987747192, 0.869701027870178],\n  [0.500023007392883, 0.190576016902924],\n  [0.499976992607117, 0.954452991485596],\n  [0.366169989109039, 0.398822009563446],\n  [0.393207013607025, 0.39553701877594],\n  [0.410373002290726, 0.391080021858215],\n  [0.194993004202843, 0.342101991176605],\n  [0.388664990663528, 0.362284004688263],\n  [0.365961998701096, 0.355970978736877],\n  [0.343364000320435, 0.355356991291046],\n  [0.318785011768341, 0.35834002494812],\n  [0.301414996385574, 0.363156020641327],\n  [0.058132998645306, 0.319076001644135],\n  [0.301414996385574, 0.387449026107788],\n  [0.499987989664078, 0.618434011936188],\n  [0.415838003158569, 0.624195992946625],\n  [0.445681989192963, 0.566076993942261],\n  [0.465844005346298, 0.620640993118286],\n  [0.49992299079895, 0.351523995399475],\n  [0.288718998432159, 0.819945991039276],\n  [0.335278987884521, 0.852819979190826],\n  [0.440512001514435, 0.902418971061707],\n  [0.128294005990028, 0.791940987110138],\n  [0.408771991729736, 0.373893976211548],\n  [0.455606997013092, 0.451801002025604],\n  [0.499877005815506, 0.908990025520325],\n  [0.375436991453171, 0.924192011356354],\n  [0.11421000212431, 0.615022003650665],\n  [0.448662012815475, 0.695277988910675],\n  [0.4480200111866, 0.704632043838501],\n  [0.447111994028091, 0.715808033943176],\n  [0.444831997156143, 0.730794012546539],\n  [0.430011987686157, 0.766808986663818],\n  [0.406787008047104, 0.685672998428345],\n  [0.400738000869751, 0.681069016456604],\n  [0.392399996519089, 0.677703022956848],\n  [0.367855995893478, 0.663918972015381],\n  [0.247923001646996, 0.601333022117615],\n  [0.452769994735718, 0.420849978923798],\n  [0.43639200925827, 0.359887003898621],\n  [0.416164010763168, 0.368713974952698],\n  [0.413385987281799, 0.692366003990173],\n  [0.228018000721931, 0.683571994304657],\n  [0.468268007040024, 0.352671027183533],\n  [0.411361992359161, 0.804327011108398],\n  [0.499989002943039, 0.469825029373169],\n  [0.479153990745544, 0.442654013633728],\n  [0.499974012374878, 0.439637005329132],\n  [0.432112008333206, 0.493588984012604],\n  [0.499886006116867, 0.866917014122009],\n  [0.49991300702095, 0.821729004383087],\n  [0.456548988819122, 0.819200992584229],\n  [0.344549000263214, 0.745438992977142],\n  [0.37890899181366, 0.574010014533997],\n  [0.374292999505997, 0.780184984207153],\n  [0.319687992334366, 0.570737957954407],\n  [0.357154995203018, 0.604269981384277],\n  [0.295284003019333, 0.621580958366394],\n  [0.447750002145767, 0.862477004528046],\n  [0.410986006259918, 0.508723020553589],\n  [0.31395098567009, 0.775308012962341],\n  [0.354128003120422, 0.812552988529205],\n  [0.324548006057739, 0.703992962837219],\n  [0.189096003770828, 0.646299958229065],\n  [0.279776990413666, 0.71465802192688],\n  [0.1338230073452, 0.682700991630554],\n  [0.336768001317978, 0.644733011722565],\n  [0.429883986711502, 0.466521978378296],\n  [0.455527991056442, 0.548622965812683],\n  [0.437114000320435, 0.558896005153656],\n  [0.467287987470627, 0.529924988746643],\n  [0.414712011814117, 0.335219979286194],\n  [0.37704598903656, 0.322777986526489],\n  [0.344107985496521, 0.320150971412659],\n  [0.312875986099243, 0.32233202457428],\n  [0.283526003360748, 0.333190023899078],\n  [0.241245999932289, 0.382785975933075],\n  [0.102986000478268, 0.468762993812561],\n  [0.267612010240555, 0.424560010433197],\n  [0.297879010438919, 0.433175981044769],\n  [0.333433985710144, 0.433878004550934],\n  [0.366427004337311, 0.426115989685059],\n  [0.396012008190155, 0.416696012020111],\n  [0.420121014118195, 0.41022801399231],\n  [0.007561000064015, 0.480777025222778],\n  [0.432949006557465, 0.569517970085144],\n  [0.458638995885849, 0.479089021682739],\n  [0.473466008901596, 0.545744001865387],\n  [0.476087987422943, 0.563830018043518],\n  [0.468472003936768, 0.555056989192963],\n  [0.433990985155106, 0.582361996173859],\n  [0.483518004417419, 0.562983989715576],\n  [0.482482999563217, 0.57784903049469],\n  [0.42645001411438, 0.389798998832703],\n  [0.438998997211456, 0.39649498462677],\n  [0.450067013502121, 0.400434017181396],\n  [0.289712011814117, 0.368252992630005],\n  [0.276670008897781, 0.363372981548309],\n  [0.517862021923065, 0.471948027610779],\n  [0.710287988185883, 0.380764007568359],\n  [0.526226997375488, 0.573909997940063],\n  [0.895093023777008, 0.254140973091125],\n  [0.634069979190826, 0.409575998783112],\n  [0.661242008209229, 0.41302502155304],\n  [0.688880026340485, 0.409460008144379],\n  [0.725341975688934, 0.389131009578705],\n  [0.606630027294159, 0.40370500087738],\n  [0.654766023159027, 0.344011008739471],\n  [0.629905998706818, 0.346076011657715],\n  [0.680678009986877, 0.347265005111694],\n  [0.702096998691559, 0.353591024875641],\n  [0.75221198797226, 0.410804986953735],\n  [0.602918028831482, 0.842862963676453],\n  [0.719901978969574, 0.375599980354309],\n  [0.893692970275879, 0.399959981441498],\n  [0.790081977844238, 0.391354024410248],\n  [0.643998026847839, 0.534487962722778],\n  [0.528249025344849, 0.65040397644043],\n  [0.525849997997284, 0.680191040039062],\n  [0.560214996337891, 0.657229006290436],\n  [0.585384011268616, 0.66654098033905],\n  [0.549625992774963, 0.680860996246338],\n  [0.57122802734375, 0.682691991329193],\n  [0.624852001667023, 0.72809898853302],\n  [0.513050019741058, 0.547281980514526],\n  [0.51509702205658, 0.527251958847046],\n  [0.742246985435486, 0.314507007598877],\n  [0.598631024360657, 0.454979002475739],\n  [0.570338010787964, 0.548575043678284],\n  [0.578631997108459, 0.533622980117798],\n  [0.723087012767792, 0.532054007053375],\n  [0.516445994377136, 0.499638974666595],\n  [0.662801027297974, 0.282917976379395],\n  [0.70362401008606, 0.293271005153656],\n  [0.830704987049103, 0.193813979625702],\n  [0.552385985851288, 0.302568018436432],\n  [0.607609987258911, 0.353887975215912],\n  [0.645429015159607, 0.696707010269165],\n  [0.932694971561432, 0.730105042457581],\n  [0.557260990142822, 0.572826027870178],\n  [0.542901992797852, 0.584792017936707],\n  [0.6180260181427, 0.694710969924927],\n  [0.607590973377228, 0.694203019142151],\n  [0.722943007946014, 0.271963000297546],\n  [0.577413976192474, 0.563166975975037],\n  [0.614082992076874, 0.281386971473694],\n  [0.616907000541687, 0.255886018276215],\n  [0.668509006500244, 0.119913995265961],\n  [0.770092010498047, 0.232020974159241],\n  [0.635536015033722, 0.189248979091644],\n  [0.77039098739624, 0.299556016921997],\n  [0.826722025871277, 0.278755009174347],\n  [0.527121007442474, 0.666198015213013],\n  [0.553171992301941, 0.668527007102966],\n  [0.577238023281097, 0.673889994621277],\n  [0.554691970348358, 0.580065965652466],\n  [0.611896991729736, 0.693961024284363],\n  [0.59696102142334, 0.706539988517761],\n  [0.596370995044708, 0.693953037261963],\n  [0.539958000183105, 0.557139039039612],\n  [0.568841993808746, 0.692366003990173],\n  [0.547818005084991, 0.692366003990173],\n  [0.52461302280426, 0.692366003990173],\n  [0.534089982509613, 0.779141008853912],\n  [0.527670979499817, 0.736225962638855],\n  [0.526912987232208, 0.717857003211975],\n  [0.526877999305725, 0.704625964164734],\n  [0.526966989040375, 0.695277988910675],\n  [0.572058022022247, 0.695277988910675],\n  [0.573521018028259, 0.703539967536926],\n  [0.57683801651001, 0.711845993995667],\n  [0.581691026687622, 0.720062971115112],\n  [0.609944999217987, 0.639909982681274],\n  [0.986046016216278, 0.560034036636353],\n  [0.5867999792099, 0.69539999961853],\n  [0.590372025966644, 0.701822996139526],\n  [0.531915009021759, 0.601536989212036],\n  [0.577268004417419, 0.585934996604919],\n  [0.536915004253387, 0.593786001205444],\n  [0.627542972564697, 0.473352015018463],\n  [0.665585994720459, 0.495950996875763],\n  [0.588353991508484, 0.546862006187439],\n  [0.757824003696442, 0.14767599105835],\n  [0.709249973297119, 0.201507985591888],\n  [0.672684013843536, 0.256581008434296],\n  [0.600408971309662, 0.74900496006012],\n  [0.55826598405838, 0.261672019958496],\n  [0.570303976535797, 0.187870979309082],\n  [0.588165998458862, 0.109044015407562],\n  [0.711045026779175, 0.398952007293701],\n  [0.781069993972778, 0.435405015945435],\n  [0.587247014045715, 0.398931980133057],\n  [0.742869973182678, 0.355445981025696],\n  [0.572156012058258, 0.437651991844177],\n  [0.55186802148819, 0.536570012569427],\n  [0.821442008018494, 0.457556009292603],\n  [0.752701997756958, 0.457181990146637],\n  [0.71375697851181, 0.467626988887787],\n  [0.66711300611496, 0.460672974586487],\n  [0.631101012229919, 0.447153985500336],\n  [0.6008620262146, 0.432473003864288],\n  [0.523481011390686, 0.405627012252808],\n  [0.810747981071472, 0.523926019668579],\n  [0.771045982837677, 0.348959028720856],\n  [0.509127020835876, 0.562718033790588],\n  [0.595292985439301, 0.485023975372314],\n  [0.980530977249146, 0.401564002037048],\n  [0.573499977588654, 0.420000016689301],\n  [0.602994978427887, 0.548687994480133],\n  [0.733529984951019, 0.376977026462555],\n  [0.560611009597778, 0.519016981124878],\n  [0.967685997486115, 0.644356966018677],\n  [0.580985009670258, 0.387160003185272],\n  [0.537728011608124, 0.505385041236877],\n  [0.760966002941132, 0.779752969741821],\n  [0.801778972148895, 0.831938028335571],\n  [0.892440974712372, 0.54076099395752],\n  [0.816350996494293, 0.740260004997253],\n  [0.865594983100891, 0.333687007427216],\n  [0.614073991775513, 0.883246004581451],\n  [0.508952975273132, 0.579437971115112],\n  [0.617941975593567, 0.508316040039062],\n  [0.825608015060425, 0.397674977779388],\n  [0.681214988231659, 0.39623498916626],\n  [0.656635999679565, 0.400596976280212],\n  [0.603900015354156, 0.710216999053955],\n  [0.81208598613739, 0.588539004325867],\n  [0.56801301240921, 0.944564998149872],\n  [0.681007981300354, 0.898285031318665],\n  [0.733752012252808, 0.869701027870178],\n  [0.633830010890961, 0.398822009563446],\n  [0.606792986392975, 0.39553701877594],\n  [0.589659988880157, 0.391062021255493],\n  [0.805015981197357, 0.342108011245728],\n  [0.611334979534149, 0.362284004688263],\n  [0.634037971496582, 0.355970978736877],\n  [0.656635999679565, 0.355356991291046],\n  [0.681214988231659, 0.35834002494812],\n  [0.698584973812103, 0.363156020641327],\n  [0.941866993904114, 0.319076001644135],\n  [0.698584973812103, 0.387449026107788],\n  [0.584177017211914, 0.624107003211975],\n  [0.554318010807037, 0.566076993942261],\n  [0.534153997898102, 0.62064003944397],\n  [0.711217999458313, 0.819975018501282],\n  [0.664629995822906, 0.852871000766754],\n  [0.559099972248077, 0.902631998062134],\n  [0.871706008911133, 0.791940987110138],\n  [0.591234028339386, 0.373893976211548],\n  [0.544341027736664, 0.451583981513977],\n  [0.624562978744507, 0.924192011356354],\n  [0.88577002286911, 0.615028977394104],\n  [0.551338016986847, 0.695277988910675],\n  [0.551980018615723, 0.704632043838501],\n  [0.552887976169586, 0.715808033943176],\n  [0.555167973041534, 0.730794012546539],\n  [0.569944024085999, 0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      resolve({ face: faceRes, body: bodyRes, hand: handRes, gesture: gestureRes, object: objectRes, performance: this.#perf, canvas: process.canvas });\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - prediction.box.topLeft[0],\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - prediction.box.topLeft[1],\n      ] : 0;\n      hands.push({ confidence: prediction.confidence, box, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.984375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.046875,\n  },\n  {\n    w: 1,\n    h: 1,\n    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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            boxRaw[0] * outputShape[0],\n            boxRaw[1] * outputShape[1],\n            boxRaw[2] * outputShape[0],\n            boxRaw[3] * outputShape[1],\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = 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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n      // rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2] - h.box[0], h.box[3] - h.box[1]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
-  "mappings": 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"../src/gender/gender.ts", "../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/decodePose.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/box.ts", "../src/handpose/handdetector.ts", "../src/handpose/util.ts", "../src/handpose/handpipeline.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/nanodet/nanodet.ts", "../src/gesture/gesture.ts", "../src/imagefx.js", "../src/image.ts", "../config.ts", "../src/sample.ts", "../src/draw.ts"],
+  "sourcesContent": ["import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModuleThreadedSimd) {\n  WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};\n\nfunction GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP32}function GROWABLE_HEAP_U32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!==\"undefined\"?WasmBackendModuleThreadedSimd:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var ENVIRONMENT_IS_PTHREAD=Module[\"ENVIRONMENT_IS_PTHREAD\"]||false;if(ENVIRONMENT_IS_PTHREAD){buffer=Module[\"buffer\"]}var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"};var nodeWorkerThreads;try{nodeWorkerThreads=require(\"worker_threads\")}catch(e){console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}global.Worker=nodeWorkerThreads.Worker}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(typeof _scriptDir !== \"undefined\" && _scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}if(ENVIRONMENT_IS_NODE){read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret}}else{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}if(ENVIRONMENT_IS_NODE){if(typeof performance===\"undefined\"){global.performance=require(\"perf_hooks\").performance}}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var Atomics_load=Atomics.load;var Atomics_store=Atomics.store;var Atomics_compareExchange=Atomics.compareExchange;var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){err(\"requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];var contextAttributes={\"alpha\":!!GROWABLE_HEAP_I32()[a+(0>>2)],\"depth\":!!GROWABLE_HEAP_I32()[a+(4>>2)],\"stencil\":!!GROWABLE_HEAP_I32()[a+(8>>2)],\"antialias\":!!GROWABLE_HEAP_I32()[a+(12>>2)],\"premultipliedAlpha\":!!GROWABLE_HEAP_I32()[a+(16>>2)],\"preserveDrawingBuffer\":!!GROWABLE_HEAP_I32()[a+(20>>2)],\"powerPreference\":__emscripten_webgl_power_preferences[powerPreference],\"failIfMajorPerformanceCaveat\":!!GROWABLE_HEAP_I32()[a+(28>>2)],majorVersion:GROWABLE_HEAP_I32()[a+(32>>2)],minorVersion:GROWABLE_HEAP_I32()[a+(36>>2)],enableExtensionsByDefault:GROWABLE_HEAP_I32()[a+(40>>2)],explicitSwapControl:GROWABLE_HEAP_I32()[a+(44>>2)],proxyContextToMainThread:GROWABLE_HEAP_I32()[a+(48>>2)],renderViaOffscreenBackBuffer:GROWABLE_HEAP_I32()[a+(52>>2)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var 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_ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"ba\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"ca\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"da\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"ea\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"fa\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"ga\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"ha\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"ia\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"ja\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"ka\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"la\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"ma\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"na\"]).apply(null,arguments)};var _Min=Module[\"_Min\"]=function(){return(_Min=Module[\"_Min\"]=Module[\"asm\"][\"oa\"]).apply(null,arguments)};var _Minimum=Module[\"_Minimum\"]=function(){return(_Minimum=Module[\"_Minimum\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var 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_OneHot=Module[\"_OneHot\"]=function(){return(_OneHot=Module[\"_OneHot\"]=Module[\"asm\"][\"wa\"]).apply(null,arguments)};var _PadV2=Module[\"_PadV2\"]=function(){return(_PadV2=Module[\"_PadV2\"]=Module[\"asm\"][\"xa\"]).apply(null,arguments)};var _Pow=Module[\"_Pow\"]=function(){return(_Pow=Module[\"_Pow\"]=Module[\"asm\"][\"ya\"]).apply(null,arguments)};var _Prelu=Module[\"_Prelu\"]=function(){return(_Prelu=Module[\"_Prelu\"]=Module[\"asm\"][\"za\"]).apply(null,arguments)};var _Prod=Module[\"_Prod\"]=function(){return(_Prod=Module[\"_Prod\"]=Module[\"asm\"][\"Aa\"]).apply(null,arguments)};var _RealDiv=Module[\"_RealDiv\"]=function(){return(_RealDiv=Module[\"_RealDiv\"]=Module[\"asm\"][\"Ba\"]).apply(null,arguments)};var _Relu=Module[\"_Relu\"]=function(){return(_Relu=Module[\"_Relu\"]=Module[\"asm\"][\"Ca\"]).apply(null,arguments)};var _Relu6=Module[\"_Relu6\"]=function(){return(_Relu6=Module[\"_Relu6\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var 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___pthread_tsd_run_dtors=Module[\"___pthread_tsd_run_dtors\"]=function(){return(___pthread_tsd_run_dtors=Module[\"___pthread_tsd_run_dtors\"]=Module[\"asm\"][\"db\"]).apply(null,arguments)};var _emscripten_main_thread_process_queued_calls=Module[\"_emscripten_main_thread_process_queued_calls\"]=function(){return(_emscripten_main_thread_process_queued_calls=Module[\"_emscripten_main_thread_process_queued_calls\"]=Module[\"asm\"][\"eb\"]).apply(null,arguments)};var _emscripten_current_thread_process_queued_calls=Module[\"_emscripten_current_thread_process_queued_calls\"]=function(){return(_emscripten_current_thread_process_queued_calls=Module[\"_emscripten_current_thread_process_queued_calls\"]=Module[\"asm\"][\"fb\"]).apply(null,arguments)};var _emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=function(){return(_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=Module[\"asm\"][\"gb\"]).apply(null,arguments)};var __emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=function(){return(__emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=Module[\"asm\"][\"hb\"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=function(){return(_emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=Module[\"asm\"][\"ib\"]).apply(null,arguments)};var _emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=function(){return(_emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=Module[\"asm\"][\"jb\"]).apply(null,arguments)};var __emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=function(){return(__emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=Module[\"asm\"][\"kb\"]).apply(null,arguments)};var _emscripten_tls_init=Module[\"_emscripten_tls_init\"]=function(){return(_emscripten_tls_init=Module[\"_emscripten_tls_init\"]=Module[\"asm\"][\"lb\"]).apply(null,arguments)};var __emscripten_thread_init=Module[\"__emscripten_thread_init\"]=function(){return(__emscripten_thread_init=Module[\"__emscripten_thread_init\"]=Module[\"asm\"][\"mb\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"nb\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"ob\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"pb\"]).apply(null,arguments)};var _emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=function(){return(_emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=Module[\"asm\"][\"qb\"]).apply(null,arguments)};var _memalign=Module[\"_memalign\"]=function(){return(_memalign=Module[\"_memalign\"]=Module[\"asm\"][\"rb\"]).apply(null,arguments)};var __emscripten_allow_main_runtime_queued_calls=Module[\"__emscripten_allow_main_runtime_queued_calls\"]=9880;var __emscripten_main_thread_futex=Module[\"__emscripten_main_thread_futex\"]=11368;Module[\"cwrap\"]=cwrap;Module[\"PThread\"]=PThread;Module[\"PThread\"]=PThread;Module[\"wasmMemory\"]=wasmMemory;Module[\"ExitStatus\"]=ExitStatus;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}if(ENVIRONMENT_IS_PTHREAD){readyPromiseResolve(Module);postMessage({\"cmd\":\"loaded\"});return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;function exit(status,implicit){if(implicit&&noExitRuntime&&status===0){return}if(!implicit){if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exitProcess\",\"returnCode\":status});throw new ExitStatus(status)}else{}}if(noExitRuntime){}else{PThread.terminateAllThreads();EXITSTATUS=status;exitRuntime();if(Module[\"onExit\"])Module[\"onExit\"](status);ABORT=true}quit_(status,new ExitStatus(status))}if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}if(ENVIRONMENT_IS_PTHREAD){noExitRuntime=false;PThread.initWorker()}run();\n\n\n  return WasmBackendModuleThreadedSimd.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModuleThreadedSimd;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModuleThreadedSimd; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd;\n", "\nvar WasmBackendModule = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModule) {\n  WasmBackendModule = WasmBackendModule || {};\n\nvar Module=typeof WasmBackendModule!==\"undefined\"?WasmBackendModule:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"}}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(_scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return 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Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). 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fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return 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false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(e){try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 0.694710969924927],\n  [0.392388999462128, 0.694203019142151],\n  [0.277076005935669, 0.271932005882263],\n  [0.422551989555359, 0.563233017921448],\n  [0.385919004678726, 0.281364023685455],\n  [0.383103013038635, 0.255840003490448],\n  [0.331431001424789, 0.119714021682739],\n  [0.229923993349075, 0.232002973556519],\n  [0.364500999450684, 0.189113974571228],\n  [0.229622006416321, 0.299540996551514],\n  [0.173287004232407, 0.278747975826263],\n  [0.472878992557526, 0.666198015213013],\n  [0.446828007698059, 0.668527007102966],\n  [0.422762006521225, 0.673889994621277],\n  [0.445307999849319, 0.580065965652466],\n  [0.388103008270264, 0.693961024284363],\n  [0.403039008378983, 0.706539988517761],\n  [0.403629004955292, 0.693953037261963],\n  [0.460041999816895, 0.557139039039612],\n  [0.431158006191254, 0.692366003990173],\n  [0.452181994915009, 0.692366003990173],\n  [0.475387006998062, 0.692366003990173],\n  [0.465828001499176, 0.779190003871918],\n  [0.472328990697861, 0.736225962638855],\n  [0.473087012767792, 0.717857003211975],\n  [0.473122000694275, 0.704625964164734],\n  [0.473033010959625, 0.695277988910675],\n  [0.427942007780075, 0.695277988910675],\n  [0.426479011774063, 0.703539967536926],\n  [0.423162013292313, 0.711845993995667],\n  [0.4183090031147, 0.720062971115112],\n  [0.390094995498657, 0.639572978019714],\n  [0.013953999616206, 0.560034036636353],\n  [0.499913990497589, 0.58014702796936],\n  [0.413199990987778, 0.69539999961853],\n  [0.409626007080078, 0.701822996139526],\n  [0.468080013990402, 0.601534962654114],\n  [0.422728985548019, 0.585985004901886],\n  [0.463079988956451, 0.593783974647522],\n  [0.37211999297142, 0.47341400384903],\n  [0.334562003612518, 0.496073007583618],\n  [0.411671012639999, 0.546965003013611],\n  [0.242175996303558, 0.14767599105835],\n  [0.290776997804642, 0.201445996761322],\n  [0.327338010072708, 0.256527006626129],\n  [0.399509996175766, 0.748921036720276],\n  [0.441727995872498, 0.261676013469696],\n  [0.429764986038208, 0.187834024429321],\n  [0.412198007106781, 0.108901023864746],\n  [0.288955003023148, 0.398952007293701],\n  [0.218936994671822, 0.435410976409912],\n  [0.41278201341629, 0.398970007896423],\n  [0.257135003805161, 0.355440020561218],\n  [0.427684992551804, 0.437960982322693],\n  [0.448339998722076, 0.536936044692993],\n  [0.178560003638268, 0.45755398273468],\n  [0.247308000922203, 0.457193970680237],\n  [0.286267012357712, 0.467674970626831],\n  [0.332827985286713, 0.460712015628815],\n  [0.368755996227264, 0.447206974029541],\n  [0.398963987827301, 0.432654976844788],\n  [0.476410001516342, 0.405806005001068],\n  [0.189241006970406, 0.523923993110657],\n  [0.228962004184723, 0.348950982093811],\n  [0.490725994110107, 0.562400996685028],\n  [0.404670000076294, 0.485132992267609],\n  [0.019469000399113, 0.401564002037048],\n  [0.426243007183075, 0.420431017875671],\n  [0.396993011236191, 0.548797011375427],\n  [0.266469985246658, 0.376977026462555],\n  [0.439121007919312, 0.51895797252655],\n  [0.032313998788595, 0.644356966018677],\n  [0.419054001569748, 0.387154996395111],\n  [0.462783008813858, 0.505746960639954],\n  [0.238978996872902, 0.779744982719421],\n  [0.198220998048782, 0.831938028335571],\n  [0.107550002634525, 0.540755033493042],\n  [0.183610007166862, 0.740257024765015],\n  [0.134409993886948, 0.333683013916016],\n  [0.385764002799988, 0.883153975009918],\n  [0.490967005491257, 0.579378008842468],\n  [0.382384985685349, 0.508572995662689],\n  [0.174399003386497, 0.397670984268188],\n  [0.318785011768341, 0.39623498916626],\n  [0.343364000320435, 0.400596976280212],\n  [0.396100014448166, 0.710216999053955],\n  [0.187885001301765, 0.588537991046906],\n  [0.430987000465393, 0.944064974784851],\n  [0.318993002176285, 0.898285031318665],\n  [0.266247987747192, 0.869701027870178],\n  [0.500023007392883, 0.190576016902924],\n  [0.499976992607117, 0.954452991485596],\n  [0.366169989109039, 0.398822009563446],\n  [0.393207013607025, 0.39553701877594],\n  [0.410373002290726, 0.391080021858215],\n  [0.194993004202843, 0.342101991176605],\n  [0.388664990663528, 0.362284004688263],\n  [0.365961998701096, 0.355970978736877],\n  [0.343364000320435, 0.355356991291046],\n  [0.318785011768341, 0.35834002494812],\n  [0.301414996385574, 0.363156020641327],\n  [0.058132998645306, 0.319076001644135],\n  [0.301414996385574, 0.387449026107788],\n  [0.499987989664078, 0.618434011936188],\n  [0.415838003158569, 0.624195992946625],\n  [0.445681989192963, 0.566076993942261],\n  [0.465844005346298, 0.620640993118286],\n  [0.49992299079895, 0.351523995399475],\n  [0.288718998432159, 0.819945991039276],\n  [0.335278987884521, 0.852819979190826],\n  [0.440512001514435, 0.902418971061707],\n  [0.128294005990028, 0.791940987110138],\n  [0.408771991729736, 0.373893976211548],\n  [0.455606997013092, 0.451801002025604],\n  [0.499877005815506, 0.908990025520325],\n  [0.375436991453171, 0.924192011356354],\n  [0.11421000212431, 0.615022003650665],\n  [0.448662012815475, 0.695277988910675],\n  [0.4480200111866, 0.704632043838501],\n  [0.447111994028091, 0.715808033943176],\n  [0.444831997156143, 0.730794012546539],\n  [0.430011987686157, 0.766808986663818],\n  [0.406787008047104, 0.685672998428345],\n  [0.400738000869751, 0.681069016456604],\n  [0.392399996519089, 0.677703022956848],\n  [0.367855995893478, 0.663918972015381],\n  [0.247923001646996, 0.601333022117615],\n  [0.452769994735718, 0.420849978923798],\n  [0.43639200925827, 0.359887003898621],\n  [0.416164010763168, 0.368713974952698],\n  [0.413385987281799, 0.692366003990173],\n  [0.228018000721931, 0.683571994304657],\n  [0.468268007040024, 0.352671027183533],\n  [0.411361992359161, 0.804327011108398],\n  [0.499989002943039, 0.469825029373169],\n  [0.479153990745544, 0.442654013633728],\n  [0.499974012374878, 0.439637005329132],\n  [0.432112008333206, 0.493588984012604],\n  [0.499886006116867, 0.866917014122009],\n  [0.49991300702095, 0.821729004383087],\n  [0.456548988819122, 0.819200992584229],\n  [0.344549000263214, 0.745438992977142],\n  [0.37890899181366, 0.574010014533997],\n  [0.374292999505997, 0.780184984207153],\n  [0.319687992334366, 0.570737957954407],\n  [0.357154995203018, 0.604269981384277],\n  [0.295284003019333, 0.621580958366394],\n  [0.447750002145767, 0.862477004528046],\n  [0.410986006259918, 0.508723020553589],\n  [0.31395098567009, 0.775308012962341],\n  [0.354128003120422, 0.812552988529205],\n  [0.324548006057739, 0.703992962837219],\n  [0.189096003770828, 0.646299958229065],\n  [0.279776990413666, 0.71465802192688],\n  [0.1338230073452, 0.682700991630554],\n  [0.336768001317978, 0.644733011722565],\n  [0.429883986711502, 0.466521978378296],\n  [0.455527991056442, 0.548622965812683],\n  [0.437114000320435, 0.558896005153656],\n  [0.467287987470627, 0.529924988746643],\n  [0.414712011814117, 0.335219979286194],\n  [0.37704598903656, 0.322777986526489],\n  [0.344107985496521, 0.320150971412659],\n  [0.312875986099243, 0.32233202457428],\n  [0.283526003360748, 0.333190023899078],\n  [0.241245999932289, 0.382785975933075],\n  [0.102986000478268, 0.468762993812561],\n  [0.267612010240555, 0.424560010433197],\n  [0.297879010438919, 0.433175981044769],\n  [0.333433985710144, 0.433878004550934],\n  [0.366427004337311, 0.426115989685059],\n  [0.396012008190155, 0.416696012020111],\n  [0.420121014118195, 0.41022801399231],\n  [0.007561000064015, 0.480777025222778],\n  [0.432949006557465, 0.569517970085144],\n  [0.458638995885849, 0.479089021682739],\n  [0.473466008901596, 0.545744001865387],\n  [0.476087987422943, 0.563830018043518],\n  [0.468472003936768, 0.555056989192963],\n  [0.433990985155106, 0.582361996173859],\n  [0.483518004417419, 0.562983989715576],\n  [0.482482999563217, 0.57784903049469],\n  [0.42645001411438, 0.389798998832703],\n  [0.438998997211456, 0.39649498462677],\n  [0.450067013502121, 0.400434017181396],\n  [0.289712011814117, 0.368252992630005],\n  [0.276670008897781, 0.363372981548309],\n  [0.517862021923065, 0.471948027610779],\n  [0.710287988185883, 0.380764007568359],\n  [0.526226997375488, 0.573909997940063],\n  [0.895093023777008, 0.254140973091125],\n  [0.634069979190826, 0.409575998783112],\n  [0.661242008209229, 0.41302502155304],\n  [0.688880026340485, 0.409460008144379],\n  [0.725341975688934, 0.389131009578705],\n  [0.606630027294159, 0.40370500087738],\n  [0.654766023159027, 0.344011008739471],\n  [0.629905998706818, 0.346076011657715],\n  [0.680678009986877, 0.347265005111694],\n  [0.702096998691559, 0.353591024875641],\n  [0.75221198797226, 0.410804986953735],\n  [0.602918028831482, 0.842862963676453],\n  [0.719901978969574, 0.375599980354309],\n  [0.893692970275879, 0.399959981441498],\n  [0.790081977844238, 0.391354024410248],\n  [0.643998026847839, 0.534487962722778],\n  [0.528249025344849, 0.65040397644043],\n  [0.525849997997284, 0.680191040039062],\n  [0.560214996337891, 0.657229006290436],\n  [0.585384011268616, 0.66654098033905],\n  [0.549625992774963, 0.680860996246338],\n  [0.57122802734375, 0.682691991329193],\n  [0.624852001667023, 0.72809898853302],\n  [0.513050019741058, 0.547281980514526],\n  [0.51509702205658, 0.527251958847046],\n  [0.742246985435486, 0.314507007598877],\n  [0.598631024360657, 0.454979002475739],\n  [0.570338010787964, 0.548575043678284],\n  [0.578631997108459, 0.533622980117798],\n  [0.723087012767792, 0.532054007053375],\n  [0.516445994377136, 0.499638974666595],\n  [0.662801027297974, 0.282917976379395],\n  [0.70362401008606, 0.293271005153656],\n  [0.830704987049103, 0.193813979625702],\n  [0.552385985851288, 0.302568018436432],\n  [0.607609987258911, 0.353887975215912],\n  [0.645429015159607, 0.696707010269165],\n  [0.932694971561432, 0.730105042457581],\n  [0.557260990142822, 0.572826027870178],\n  [0.542901992797852, 0.584792017936707],\n  [0.6180260181427, 0.694710969924927],\n  [0.607590973377228, 0.694203019142151],\n  [0.722943007946014, 0.271963000297546],\n  [0.577413976192474, 0.563166975975037],\n  [0.614082992076874, 0.281386971473694],\n  [0.616907000541687, 0.255886018276215],\n  [0.668509006500244, 0.119913995265961],\n  [0.770092010498047, 0.232020974159241],\n  [0.635536015033722, 0.189248979091644],\n  [0.77039098739624, 0.299556016921997],\n  [0.826722025871277, 0.278755009174347],\n  [0.527121007442474, 0.666198015213013],\n  [0.553171992301941, 0.668527007102966],\n  [0.577238023281097, 0.673889994621277],\n  [0.554691970348358, 0.580065965652466],\n  [0.611896991729736, 0.693961024284363],\n  [0.59696102142334, 0.706539988517761],\n  [0.596370995044708, 0.693953037261963],\n  [0.539958000183105, 0.557139039039612],\n  [0.568841993808746, 0.692366003990173],\n  [0.547818005084991, 0.692366003990173],\n  [0.52461302280426, 0.692366003990173],\n  [0.534089982509613, 0.779141008853912],\n  [0.527670979499817, 0.736225962638855],\n  [0.526912987232208, 0.717857003211975],\n  [0.526877999305725, 0.704625964164734],\n  [0.526966989040375, 0.695277988910675],\n  [0.572058022022247, 0.695277988910675],\n  [0.573521018028259, 0.703539967536926],\n  [0.57683801651001, 0.711845993995667],\n  [0.581691026687622, 0.720062971115112],\n  [0.609944999217987, 0.639909982681274],\n  [0.986046016216278, 0.560034036636353],\n  [0.5867999792099, 0.69539999961853],\n  [0.590372025966644, 0.701822996139526],\n  [0.531915009021759, 0.601536989212036],\n  [0.577268004417419, 0.585934996604919],\n  [0.536915004253387, 0.593786001205444],\n  [0.627542972564697, 0.473352015018463],\n  [0.665585994720459, 0.495950996875763],\n  [0.588353991508484, 0.546862006187439],\n  [0.757824003696442, 0.14767599105835],\n  [0.709249973297119, 0.201507985591888],\n  [0.672684013843536, 0.256581008434296],\n  [0.600408971309662, 0.74900496006012],\n  [0.55826598405838, 0.261672019958496],\n  [0.570303976535797, 0.187870979309082],\n  [0.588165998458862, 0.109044015407562],\n  [0.711045026779175, 0.398952007293701],\n  [0.781069993972778, 0.435405015945435],\n  [0.587247014045715, 0.398931980133057],\n  [0.742869973182678, 0.355445981025696],\n  [0.572156012058258, 0.437651991844177],\n  [0.55186802148819, 0.536570012569427],\n  [0.821442008018494, 0.457556009292603],\n  [0.752701997756958, 0.457181990146637],\n  [0.71375697851181, 0.467626988887787],\n  [0.66711300611496, 0.460672974586487],\n  [0.631101012229919, 0.447153985500336],\n  [0.6008620262146, 0.432473003864288],\n  [0.523481011390686, 0.405627012252808],\n  [0.810747981071472, 0.523926019668579],\n  [0.771045982837677, 0.348959028720856],\n  [0.509127020835876, 0.562718033790588],\n  [0.595292985439301, 0.485023975372314],\n  [0.980530977249146, 0.401564002037048],\n  [0.573499977588654, 0.420000016689301],\n  [0.602994978427887, 0.548687994480133],\n  [0.733529984951019, 0.376977026462555],\n  [0.560611009597778, 0.519016981124878],\n  [0.967685997486115, 0.644356966018677],\n  [0.580985009670258, 0.387160003185272],\n  [0.537728011608124, 0.505385041236877],\n  [0.760966002941132, 0.779752969741821],\n  [0.801778972148895, 0.831938028335571],\n  [0.892440974712372, 0.54076099395752],\n  [0.816350996494293, 0.740260004997253],\n  [0.865594983100891, 0.333687007427216],\n  [0.614073991775513, 0.883246004581451],\n  [0.508952975273132, 0.579437971115112],\n  [0.617941975593567, 0.508316040039062],\n  [0.825608015060425, 0.397674977779388],\n  [0.681214988231659, 0.39623498916626],\n  [0.656635999679565, 0.400596976280212],\n  [0.603900015354156, 0.710216999053955],\n  [0.81208598613739, 0.588539004325867],\n  [0.56801301240921, 0.944564998149872],\n  [0.681007981300354, 0.898285031318665],\n  [0.733752012252808, 0.869701027870178],\n  [0.633830010890961, 0.398822009563446],\n  [0.606792986392975, 0.39553701877594],\n  [0.589659988880157, 0.391062021255493],\n  [0.805015981197357, 0.342108011245728],\n  [0.611334979534149, 0.362284004688263],\n  [0.634037971496582, 0.355970978736877],\n  [0.656635999679565, 0.355356991291046],\n  [0.681214988231659, 0.35834002494812],\n  [0.698584973812103, 0.363156020641327],\n  [0.941866993904114, 0.319076001644135],\n  [0.698584973812103, 0.387449026107788],\n  [0.584177017211914, 0.624107003211975],\n  [0.554318010807037, 0.566076993942261],\n  [0.534153997898102, 0.62064003944397],\n  [0.711217999458313, 0.819975018501282],\n  [0.664629995822906, 0.852871000766754],\n  [0.559099972248077, 0.902631998062134],\n  [0.871706008911133, 0.791940987110138],\n  [0.591234028339386, 0.373893976211548],\n  [0.544341027736664, 0.451583981513977],\n  [0.624562978744507, 0.924192011356354],\n  [0.88577002286911, 0.615028977394104],\n  [0.551338016986847, 0.695277988910675],\n  [0.551980018615723, 0.704632043838501],\n  [0.552887976169586, 0.715808033943176],\n  [0.555167973041534, 0.730794012546539],\n  [0.569944024085999, 0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    boxRaw: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.#perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: prediction.confidence, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            Math.max(0, (boxRaw[0] * outputShape[0])),\n            Math.max(0, (boxRaw[1] * outputShape[1])),\n            Math.min(1, (boxRaw[2] * outputShape[0]) - (boxRaw[0] * outputShape[0])),\n            Math.min(1, (boxRaw[3] * outputShape[1]) - (boxRaw[1] * outputShape[1])),\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
+  "mappings": 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   "names": []
 }
diff --git a/dist/human.js b/dist/human.js
index 8138c96a..3eafe10f 100644
--- a/dist/human.js
+++ b/dist/human.js
@@ -5,31 +5,31 @@
   author: <https://github.com/vladmandic>'
   */
 
-var Human=(()=>{var v8=Object.create,Ah=Object.defineProperty,k8=Object.getPrototypeOf,N8=Object.prototype.hasOwnProperty,I8=Object.getOwnPropertyNames,S8=Object.getOwnPropertyDescriptor;var Q1=e=>Ah(e,"__esModule",{value:!0});var Lg=(e,t)=>()=>(t||(t={exports:{}},e(t.exports,t)),t.exports),Gn=(e,t)=>{for(var n in t)Ah(e,n,{get:t[n],enumerable:!0})},T8=(e,t,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of I8(t))!N8.call(e,r)&&r!=="default"&&Ah(e,r,{get:()=>t[r],enumerable:!(n=S8(t,r))||n.enumerable});return e},yh=e=>T8(Q1(Ah(e!=null?v8(k8(e)):{},"default",e&&e.__esModule&&"default"in e?{get:()=>e.default,enumerable:!0}:{value:e,enumerable:!0})),e);var Wg=(e,t,n)=>{if(!t.has(e))throw TypeError("Cannot "+n)},me=(e,t,n)=>(Wg(e,t,"read from private field"),n?n.call(e):t.get(e)),ta=(e,t,n,r)=>(Wg(e,t,"write to private field"),r?r.call(e,n):t.set(e,n),n);var E6=Lg(C6=>{Q1(C6);Gn(C6,{MediaPipeFaceMesh:()=>k2,load:()=>zae});var k2=class{constructor(t,n,r,a){this.facePipeline=new v2(t,n,r),this.config=a}async estimateFaces(t,n){let r=await this.facePipeline.predict(t,n),a=[];for(let s of r||[]){if(s.isDisposedInternal)continue;let i=s.coords?s.coords.arraySync():[],o=i.map(h=>[h[0]/t.shape[2],h[1]/t.shape[1],h[2]/this.facePipeline.meshSize]),l={};if(i&&i.length>0)for(let h of Object.keys(Xr))l[h]=Xr[h].map(d=>i[d]);let u=s.box?[Math.max(0,s.box.startPoint[0]),Math.max(0,s.box.startPoint[1]),Math.min(t.shape[1],s.box.endPoint[0])-s.box.startPoint[0],Math.min(t.shape[2],s.box.endPoint[1])-s.box.startPoint[1]]:0,c=s.box?[Math.max(0,s.box.startPoint[0]/t.shape[2]),Math.max(0,s.box.startPoint[1]/t.shape[1]),Math.min(t.shape[1],s.box.endPoint[0]-s.box.startPoint[0])/t.shape[2],Math.min(t.shape[2],s.box.endPoint[1]-s.box.startPoint[1])/t.shape[1]]:[];a.push({confidence:s.faceConfidence||s.boxConfidence||0,boxConfidence:s.boxConfidence,faceConfidence:s.faceConfidence,box:u,mesh:i,boxRaw:c,meshRaw:o,annotations:l,image:s.image?s.image.clone():null}),s.coords&&s.coords.dispose(),s.image&&s.image.dispose()}return a}},$i=[null,null,null];async function zae(e){$i=await Promise.all([!$i[0]&&e.face.enabled?b6(e):null,!$i[1]&&e.face.mesh.enabled?Tt(e.face.mesh.modelPath,{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!$i[2]&&e.face.iris.enabled?Tt(e.face.iris.modelPath,{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]);let t=new k2($i[0],$i[1],$i[2],e);return e.face.mesh.enabled&&e.debug&&Ee(`load model: ${e.face.mesh.modelPath.match(/\/(.*)\./)[1]}`),e.face.iris.enabled&&e.debug&&Ee(`load model: ${e.face.iris.modelPath.match(/\/(.*)\./)[1]}`),t}C6.triangulation=Mi});var x0=Lg(q2=>{Q1(q2);Gn(q2,{NUM_KEYPOINTS:()=>Vae,connectedPartIndices:()=>jae,partChannels:()=>Gae,partIds:()=>X2,partNames:()=>Bae,poseChain:()=>Hae});var 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r=++this.pendingBackendInitId,a=n.then(s=>r<this.pendingBackendInitId?!1:(this.registry[e]=s,this.pendingBackendInit=null,!0)).catch(s=>(r<this.pendingBackendInitId||(this.pendingBackendInit=null,console.warn(`Initialization of backend ${e} failed`),console.warn(s.stack||s.message)),!1));return this.pendingBackendInit=a,{success:a,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return console.warn(`Initialization of backend ${e} failed`),console.warn(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t],{success:r,asyncInit:a}=this.initializeBackend(n);if(a||r)return{name:n,asyncInit:a}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),r=n.backend,a=this.readSync(t),s=r.refCount(t);r.disposeData(t,!0),n.backend=e,e.move(t,a,n.shape,n.dtype,s),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");n=e}let r;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(r),()=>(r=t(),r instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),r))}scopedRun(e,t,n){e();try{let r=n();return t(),r}catch(r){throw t(),r}}nextTensorId(){return Mu.nextTensorId++}nextVariableId(){return Mu.nextVariableId++}clone(e){let t=$.runKernel(Ns,{x:e}),n={x:e},r=s=>({x:()=>{let i="float32",o={x:s},l={dtype:i};return $.runKernel(ds,o,l)}}),a=[];return this.addTapeNode(this.state.activeScope.name,n,[t],r,a,{}),t}runKernel(e,t,n){if(nd(e,this.backendName)==null)throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let r=this.backend.numDataIds(),a=0;n.forEach(o=>{a+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=r-t-a-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],r=this.isTapeOn(),a=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=yf(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(yf(e)){let{kernelName:p,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let A=nd(p,this.backendName);F(A!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),i=()=>{let y=this.backend.numDataIds();o=A.kernelFunc({inputs:f,attrs:m,backend:this.backend});let g=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,y,g);let w=g.map(b=>{if(b.rank!=null)return b;let{dataId:_,shape:x,dtype:I}=b;return this.makeTensorFromDataId(_,x,I)});if(r){let b=this.getTensorsForGradient(p,f,w);n=this.saveTensorsForBackwardMode(b)}return w}}else{let{forwardFunc:p}=e,f=m=>{!r||(n=m.map(A=>this.keep(this.clone(A))))};i=()=>{let m=this.backend.numDataIds();o=this.tidy(()=>p(this.backend,f));let A=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,A),A}}let{inputs:u,attrs:c}=e,h=yf(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(d=this.profiler.profileKernel(l,u,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),r&&this.addTapeNode(l,u,t,h,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(p=>u[p]!=null?u[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let r=uf(e);if(r!=null){let a=r.inputsToSave||[],s=r.outputsToSave||[],i;r.saveAllInputs?(F(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let o=n.filter((l,u)=>s[u]);return i.concat(o)}return[]}makeTensor(e,t,n,r){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",r=r||this.backend;let a=e;n==="string"&&ka(e[0])&&(a=e.map(o=>Tu(o)));let s=r.write(a,t,n),i=new je(t,n,s,this.nextTensorId());if(this.trackTensor(i,r),n==="string"){let o=this.state.tensorInfo.get(s),l=Kg(a);this.state.numBytes+=l-o.bytes,o.bytes=l}return i}makeTensorFromDataId(e,t,n,r){n=n||"float32";let a=new je(t,n,e,this.nextTensorId());return this.trackTensor(a,r),a}makeVariable(e,t=!0,n,r){n=n||this.nextVariableId().toString(),r!=null&&r!==e.dtype&&(e=e.cast(r));let a=new Fu(e,t,n,this.nextTensorId());if(this.state.registeredVariables[a.name]!=null)throw new Error(`Variable with name ${a.name} was already registered`);return this.state.registeredVariables[a.name]=a,this.incRef(a,this.backend),a}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*tf(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 Fu||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*tf(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,a,s){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:a},o=uf(e);o!=null&&(r=o.gradFunc),r!=null&&(i.gradient=l=>(l=l.map((u,c)=>{if(u==null){let h=n[c],d=vh(h.size,h.dtype);return this.makeTensor(d,h.shape,h.dtype)}return u}),r(l.length>1?l:l[0],a,s))),this.state.activeTape.push(i)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=hf(e),n=new Set(t.map(a=>a.id));for(let a=0;a<this.state.activeScope.track.length;a++){let s=this.state.activeScope.track[a];!s.kept&&!n.has(s.id)&&s.dispose()}let r=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(a=>{!a.kept&&a.scopeId===r.id&&this.track(a)})}gradients(e,t,n,r=!1){if(F(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let a=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));F(a instanceof je,()=>"The result y returned by f() must be a tensor.");let s=Xk(this.state.activeTape,t,a);if(!r&&s.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{let i={};i[a.id]=n==null?s9(a.shape):n,Kk(i,s,l=>this.tidy(l),i9);let o=t.map(l=>i[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:a,grads:o}})}customGrad(e){return F(Na(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{F(t.every(i=>i instanceof je),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,r={};t.forEach((i,o)=>{r[o]=i});let a=(i,o)=>(n=e(...t,o),F(n.value instanceof je,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),F(Na(n.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),n.value),s=(i,o)=>{let l=n.gradFunc(i,o),u=Array.isArray(l)?l:[l];F(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(...)."),F(u.every(h=>h instanceof je),()=>"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((h,d)=>{c[d]=()=>h}),c};return this.runKernelFunc({forwardFunc:a,backwardsFunc:s,inputs:r})}}readSync(e){return this.state.tensorInfo.get(e).backend.readSync(e)}read(e){return this.state.tensorInfo.get(e).backend.read(e)}async time(e){let t=Su(),n=await this.backend.time(e);return n.wallMs=Su()-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 u5;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}};Mu.nextTensorId=0;Mu.nextVariableId=0;function s9(e){let t=nf(Ot(e),"float32");return $.makeTensor(t,e,"float32")}function c5(){let e=t5();if(e._tfengine==null){let t=new e5(e);e._tfengine=new Mu(t)}return Ok(e._tfengine.ENV),Qk(()=>e._tfengine),e._tfengine}var $=c5();function i9(e,t){let n={a:e,b:t};return $.runKernel(Ia,n)}var $u={};ze($u,{isBrowser:()=>h5,isMobile:()=>o9});function l9(){return typeof navigator!="undefined"&&navigator!=null}function o9(){if(l9()){let e=navigator.userAgent||navigator.vendor||window.opera;return/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(e)||/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(e.substr(0,4))}return!1}function h5(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var gr=J();gr.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. 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bM={kernelName:ms,backendName:"cpu",kernelFunc:_M};function vM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r;be([a,s],"conv3d");let u=R.computeConv3DInfo(a.shape,s.shape,i,l,o),{filterDepth:c,filterHeight:h,filterWidth:d,dilationDepth:p,dilationHeight:f,dilationWidth:m,padInfo:A}=u,y=A.front,g=A.left,w=A.top,b=new zt(u.outShape,a.dtype),_=n.data.get(a.dataId).values,x=n.data.get(s.dataId).values,I=b.values,S=v.computeStrides(a.shape),T=v.computeStrides(s.shape);for(let M=0;M<u.batchSize;++M){let D=M*S[0],z=M*b.strides[0];for(let B=0;B<u.outDepth;++B){let U=z+B*b.strides[1],j=B*u.strideDepth-y;for(let X=0;X<c;++X){let H=j+X*p;if(H<0||H>=u.inDepth)continue;let ee=X*T[0],Y=D+H*S[1];for(let ae=0;ae<u.outHeight;++ae){let te=U+ae*b.strides[2],ie=ae*u.strideHeight-w;for(let Q=0;Q<h;++Q){let he=ie+Q*f;if(he<0||he>=u.inHeight)continue;let le=ee+Q*T[1],fe=Y+he*S[2];for(let pe=0;pe<u.outWidth;++pe){let ke=te+pe*u.outChannels,Ie=pe*u.strideWidth-g;for(let 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zM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.data.get(a.dataId).values,u=n.data.get(s.dataId).values,c=Cm(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=Xx(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var PM={kernelName:Mh,backendName:"cpu",kernelFunc:zM};function LM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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RM={kernelName:cu,backendName:"cpu",kernelFunc:EM},MM=st(eo,e=>Math.asin(e)),FM={kernelName:eo,backendName:"cpu",kernelFunc:MM},$M=st(to,e=>Math.asinh(e)),DM={kernelName:to,backendName:"cpu",kernelFunc:$M},OM=st(no,e=>Math.atan(e)),zM={kernelName:no,backendName:"cpu",kernelFunc:OM},PM=Ft((e,t)=>Math.atan2(e,t)),LM=qt(ao,PM),WM={kernelName:ao,backendName:"cpu",kernelFunc:LM},BM=st(ro,e=>Math.atanh(e)),VM={kernelName:ro,backendName:"cpu",kernelFunc:BM};function Pm(e,t,n,r,a,s){let i=a.strideHeight,o=a.strideWidth,l=a.dilationHeight,c=a.dilationWidth,u=a.effectiveFilterHeight,h=a.effectiveFilterWidth,d=a.padInfo.top,p=a.padInfo.left,f=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=We(a.outShape,n),A=m.values,y=a.outShape[1]*a.outShape[2]*a.outShape[3],g=a.outShape[2]*a.outShape[3],w=a.outShape[3];for(let b=0;b<a.batchSize;++b){let _=b*y,x=b*r[0];for(let N=0;N<a.inChannels;++N)for(let T=0;T<a.outHeight;++T){let 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CF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.data.get(a.dataId).values,c=n.data.get(s.dataId).values,u=Cm(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=Kx(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var EF={kernelName:$h,backendName:"cpu",kernelFunc:CF};function RF(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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$F(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r;_e([a,s],"depthwiseConv2dNativeBackpropFilter");let h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),{strideHeight:d,strideWidth:p,filterHeight:f,filterWidth:m}=h,A=new zt(h.filterShape,"float32"),y=h.padInfo.left,g=h.padInfo.top,w=h.outChannels/h.inChannels,b=n.data.get(a.dataId).values,_=new zt(a.shape,a.dtype,b),x=n.data.get(s.dataId).values,N=new zt(s.shape,s.dtype,x);for(let T=0;T<f;++T){let C=Math.max(0,Math.ceil((g-T)/d)),F=Math.min(h.outHeight,(h.inHeight+g-T)/d);for(let z=0;z<m;++z){let B=Math.max(0,Math.ceil((y-z)/p)),V=Math.min(h.outWidth,(h.inWidth+y-z)/p);for(let U=0;U<h.outChannels;++U){let j=Math.trunc(U/w),X=U%w,G=0;for(let ee=0;ee<h.batchSize;++ee)for(let Y=C;Y<F;++Y){let ae=T+Y*d-g;for(let te=B;te<V;++te){let oe=z+te*p-y;G+=_.get(ee,ae,oe,j)*N.get(ee,Y,te,U)}}A.set(G,T,z,j,X)}}}return n.makeTensorInfo(A.shape,A.dtype,A.values)}var DF={kernelName:Dh,backendName:"cpu",kernelFunc:$F};function OF(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r;_e([a,s],"depthwiseConv2DNativeBackpropInput");let h=v.computeStrides(a.shape),d=v.computeStrides(s.shape),p=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),f=new zt(p.inShape,"float32"),m=f.values,[A,y,g]=f.strides,w=n.data.get(a.dataId).values,[b,_,x]=h,N=n.data.get(s.dataId).values,[T,C,F]=d,{batchSize:z,filterHeight:B,filterWidth:V,inChannels:U,inHeight:j,inWidth:X,outChannels:G,outHeight:ee,outWidth:Y,strideHeight:ae,strideWidth:te}=p,oe=B-1-p.padInfo.top,Q=V-1-p.padInfo.left,he=G/U;for(let le=0;le<z;++le)for(let fe=0;fe<U;++fe)for(let pe=0;pe<j;++pe){let ke=pe-oe,Ne=Math.max(0,Math.ceil(ke/ae)),Fe=Math.min(ee,(B+ke)/ae);for(let Oe=0;Oe<X;++Oe){let $e=Oe-Q,et=Math.max(0,Math.ceil($e/te)),tt=Math.min(Y,(V+$e)/te),ot=0;for(let Ye=Ne;Ye<Fe;++Ye){let dt=Ye*ae-ke;for(let Be=et;Be<tt;++Be){let yn=Be*te-$e,wt=b*le+_*Ye+x*Be,Un=T*(B-1-dt)+C*(V-1-yn)+F*fe;for(let Yt=0;Yt<he;++Yt){let gn=fe*he+Yt,jn=w[wt+gn],Rn=N[Un+Yt];ot+=jn*Rn}}}m[A*le+y*pe+g*Oe+fe]=ot}}return n.makeTensorInfo(f.shape,f.dtype,f.values)}var zF={kernelName:Oh,backendName:"cpu",kernelFunc:OF};function PF(e){let{inputs:t,backend:n}=e,{x:r}=t,a=v.sizeFromShape(r.shape),s=n.data.get(r.dataId).values,i=We([a,a],r.dtype),o=i.values;for(let c=0;c<s.length;c++)o[c*a+c]=s[c];let l=[...r.shape,...r.shape];return n.makeTensorInfo(l,i.dtype,i.values)}var 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e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function ua(e,t,n){let r=we(e,()=>t());if(r==null)throw new Error(n);return r}function cb(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,r=t+e.TEXTURE0;if(r<e.TEXTURE0||r>n){let a=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${a}.`)}}function gi(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function xi(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function ip(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[gi(e),...xi(e)]),t}function rb(e,t=!1){let n=J().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((a,s)=>s>=e.length-2?v.nearestLargerEven(e[s]):e[s]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let r=v.sizeFromShape(e);if(e.length<=1&&r<=n)return[1,r];if(e.length===2&&e[0]<=n&&e[1]<=n)return e;if(e.length===3&&e[0]*e[1]<=n&&e[2]<=n)return[e[0]*e[1],e[2]];if(e.length===3&&e[0]<=n&&e[1]*e[2]<=n)return[e[0],e[1]*e[2]];if(e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n)return[e[0]*e[1]*e[2],e[3]];if(e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n)return[e[0],e[1]*e[2]*e[3]];if(t){let a=gi(e),s=2,i=2;return e.length&&([s,i]=xi(e)),r=a*(s/2)*(i/2),v.sizeToSquarishShape(r).map(o=>o*2)}return v.sizeToSquarishShape(r)}function lp(e){return e%2==0}function oc(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e.slice(-1)[0],r=t.slice(-1)[0];if(n===r||lp(n)&&lp(r)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&lp(e[0])&&lp(t[0])}var up,cp;function ab(e){if(up==null){let t=Vr(e);up=t.getParameter(t.MAX_TEXTURE_SIZE)}return up}function lz(){up=null}function uz(){cp=null}function sb(e){if(cp==null){let t=Vr(e);cp=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,cp)}function ib(e){if(e===0)return 0;let t,n=Vr(e);return Yn(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:Yn(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function Yn(e,t){return e.getExtension(t)!=null}function Hm(e){try{if(Vr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function ob(e){if(e===0)return!1;let t=Vr(e);if(e===1){if(!Yn(t,"OES_texture_float"))return!1}else if(!Yn(t,"EXT_color_buffer_float"))return!1;return Xm(t)}function lb(e){if(e===0)return!1;let t=Vr(e);if(e===1){if(!Yn(t,"OES_texture_float")||!Yn(t,"WEBGL_color_buffer_float"))return!1}else{if(Yn(t,"EXT_color_buffer_float"))return Xm(t);let n="EXT_color_buffer_half_float";if(Yn(t,n)){let r=t.getExtension(n);return xz(t,r)}return!1}return Xm(t)}function Xm(e){let t=qm(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,r,a,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(s),i}function xz(e,t){let n=qm(e,t),r=e.createTexture();e.bindTexture(e.TEXTURE_2D,r);let a=1,s=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,a,s,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,r,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(r),e.deleteFramebuffer(i),o}function ub(e){return e!==2?!1:Vr(e).fenceSync!=null}function kl(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Me=J();Me.registerFlag("HAS_WEBGL",()=>Me.getNumber("WEBGL_VERSION")>0);Me.registerFlag("WEBGL_VERSION",()=>Hm(2)?2:Hm(1)?1:0);Me.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Me.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Me.get("WEBGL_VERSION")===2);Me.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Me.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Me.registerFlag("WEBGL_PACK",()=>Me.getBool("HAS_WEBGL"));Me.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_CLIP",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>!1);Me.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_PACK_REDUCE",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_LAZILY_UNPACK",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_CONV_IM2COL",()=>Me.getBool("WEBGL_PACK"));Me.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>ab(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>sb(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Me.getNumber("WEBGL_VERSION");return e===0?0:ib(e)});Me.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Me.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Du.isMobile());Me.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>ob(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Me.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Me.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Me.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>lb(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_FENCE_API_ENABLED",()=>ub(Me.getNumber("WEBGL_VERSION")));Me.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Me.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Me.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});Me.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Du.isMobile()&&Me.getBool("IS_CHROME")?1:-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});function fn(){let e,t,n,r,a,s,i,o,l,c;return J().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",r="in",a="texture",s="outputColor",i="out vec4 outputColor;",o=`
       bool isnan_custom(float val) {
         return (val > 0.0 || val < 0.0) ? false : val != 0.0;
       }
@@ -40,7 +40,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       }
 
       #define isnan(value) isnan_custom(value)
-    `,l="",u=`
+    `,l="",c=`
       #define round(value) newRound(value)
       int newRound(float value) {
         return int(floor(value + 0.5));
@@ -66,7 +66,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       bvec4 isinf(vec4 val) {
         return equal(abs(val), vec4(INFINITY));
       }
-    `,u=`
+    `,c=`
       int round(float value) {
         return int(floor(value + 0.5));
       }
@@ -74,11 +74,11 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       ivec4 round(vec4 value) {
         return ivec4(floor(value + vec4(0.5)));
       }
-    `),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:u}}function _i(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function Km(e){let t=v.computeStrides(e).map(n=>n.toString());return`
+    `),{version:e,attribute:t,varyingVs:n,varyingFs:r,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:c}}function bi(e,t,n="index"){let r=v.computeStrides(t);return r.map((a,s)=>{let i=`int ${e[s]} = ${n} / ${a}`,o=s===r.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function Km(e){let t=v.computeStrides(e).map(n=>n.toString());return`
   int getFlatIndex(ivec3 coords) {
     return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
   }
-`}var c_=`
+`}var hb=`
   const float FLOAT_MAX = 1.70141184e38;
   const float FLOAT_MIN = 1.17549435e-38;
 
@@ -117,9 +117,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
     return c / 255.0;
   }
-`,Tz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=oc.DENSE;let t=uc(e),n=fn();this.outputShape=e,this.userCode=`
+`,wz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=lc.DENSE;let t=cc(e),n=fn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${_i(["r","c","d"],e)}
+        ${bi(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -138,9 +138,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},Cz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=oc.DENSE;let t=uc(e),n=fn();this.outputShape=e,this.userCode=`
+    `}},bz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=lc.DENSE;let t=cc(e),n=fn();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${_i(["r","c","d"],e)}
+        ${bi(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -159,22 +159,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${n.output} = result;
       }
-    `}},Ez=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Jn.DOWNLOAD;let t=fn();this.outputShape=e,this.userCode=`
-      ${c_}
+    `}},_z=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Jn.DOWNLOAD;let t=fn();this.outputShape=e,this.userCode=`
+      ${hb}
 
       void main() {
         float x = getAAtOutCoords();
         ${t.output} = encode_float(x);
       }
-    `}},Rz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Jn.DOWNLOAD;let t=fn();this.outputShape=e,this.userCode=`
-      ${c_}
+    `}},vz=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Jn.DOWNLOAD;let t=fn();this.outputShape=e,this.userCode=`
+      ${hb}
 
       void main() {
         ivec3 coords = getOutputCoords();
         float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
         ${t.output} = encode_float(x);
       }
-    `}},Fz=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=fn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
+    `}},kz=class{constructor(e,t,n=!1){this.variableNames=["A"];let r=fn(),[a,s]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
       ${Km(e)}
 
       void main() {
@@ -204,10 +204,10 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = vec4(${i}, 0., 0., 0.);
       }
-    `}},Mz=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=fn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let u=0;u<=1;u++){let c=l*2+u;i+=`
+    `}},Iz=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let r=fn(),[a,s]=t;this.outputShape=e;let i="",o="result";n&&(o="floor(result * 255. + 0.5)");for(let l=0;l<=1;l++)for(let c=0;c<=1;c++){let u=l*2+c;i+=`
           localCoords = coords;
-          if(localCoords[2] + ${u} < ${e[2]}) {
-            localCoords[2] += ${u};
+          if(localCoords[2] + ${c} < ${e[2]}) {
+            localCoords[2] += ${c};
             if(localCoords[1] + ${l} < ${e[1]}) {
               localCoords[1] += ${l};
 
@@ -222,13 +222,13 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
               values = ${r.texture2D}(A, uv);
 
               if(offset == 0) {
-                result[${c}] = values[0];
+                result[${u}] = values[0];
               } else if(offset == 1) {
-                result[${c}] = values[1];
+                result[${u}] = values[1];
               } else if(offset == 2) {
-                result[${c}] = values[2];
+                result[${u}] = values[2];
               } else {
-                result[${c}] = values[3];
+                result[${u}] = values[3];
               }
             }
           }
@@ -248,7 +248,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${r.output} = ${o};
       }
-    `}},h_={};ze(h_,{bindVertexProgramAttributeStreams:()=>w_,createBufferFromOutputTexture:()=>v_,createFloat16MatrixTexture:()=>A_,createFloat16PackedMatrixTexture:()=>x_,createFloat32MatrixTexture:()=>m_,createIndexBuffer:()=>f_,createPackedMatrixTexture:()=>g_,createUnsignedBytesMatrixTexture:()=>y_,createVertexBuffer:()=>p_,createVertexShader:()=>d_,downloadByteEncodedFloatMatrixFromOutputTexture:()=>N_,downloadFloat32MatrixFromBuffer:()=>k_,downloadMatrixFromPackedOutputTexture:()=>S_,downloadPackedMatrixFromBuffer:()=>I_,getInternalFormatForFloat16MatrixTexture:()=>Ym,getInternalFormatForFloat16PackedMatrixTexture:()=>eA,getInternalFormatForFloat32MatrixTexture:()=>Zm,getInternalFormatForPackedMatrixTexture:()=>Qm,getInternalFormatForUnsignedBytesMatrixTexture:()=>Jm,uploadDenseMatrixToTexture:()=>__,uploadPixelDataToTexture:()=>b_});function d_(e){let t=fn(),n=`${t.version}
+    `}},db={};ze(db,{bindVertexProgramAttributeStreams:()=>bb,createBufferFromOutputTexture:()=>kb,createFloat16MatrixTexture:()=>yb,createFloat16PackedMatrixTexture:()=>wb,createFloat32MatrixTexture:()=>Ab,createIndexBuffer:()=>mb,createPackedMatrixTexture:()=>xb,createUnsignedBytesMatrixTexture:()=>gb,createVertexBuffer:()=>fb,createVertexShader:()=>pb,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Nb,downloadFloat32MatrixFromBuffer:()=>Ib,downloadMatrixFromPackedOutputTexture:()=>Tb,downloadPackedMatrixFromBuffer:()=>Sb,getInternalFormatForFloat16MatrixTexture:()=>Ym,getInternalFormatForFloat16PackedMatrixTexture:()=>eA,getInternalFormatForFloat32MatrixTexture:()=>Zm,getInternalFormatForPackedMatrixTexture:()=>Qm,getInternalFormatForUnsignedBytesMatrixTexture:()=>Jm,uploadDenseMatrixToTexture:()=>_b,uploadPixelDataToTexture:()=>vb});function pb(e){let t=fn(),n=`${t.version}
     precision highp float;
     ${t.attribute} vec3 clipSpacePos;
     ${t.attribute} vec2 uv;
@@ -257,22 +257,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
     void main() {
       gl_Position = vec4(clipSpacePos, 1);
       resultUV = uv;
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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;we(e,()=>e.finish()),we(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),we(e,()=>e.deleteFramebuffer(this.framebuffer)),we(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),we(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),we(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),Ab(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),yb(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),gb(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),vb(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,r){this.throwIfDisposed(),_b(this.gl,e,t,n,r,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),wb(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),xb(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(jm(this.gl,this.framebuffer),this.outputTexture=null),we(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Nb(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,r,a,s){return Sb(this.gl,e,t,n,r,a,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return Ib(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let r=kb(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(J().getBool("WEBGL_FENCE_API_ENABLED")){let r=e,a=r.fenceSync(r.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let s=r.clientWaitSync(a,0,0);return s===r.ALREADY_SIGNALED||s===r.CONDITION_SATISFIED},t=a}else J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>Tb(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=jw(t,e),r=pb(t),a=Hw(t);return we(t,()=>t.attachShader(a,r)),we(t,()=>t.attachShader(a,n)),Gw(t,a),this.debug&&ap(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=bb(t,this.program,this.vertexBuffer)),a}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&we(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&ap(this.gl,this.program),we(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?Qw(this.gl,e,t):eb(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),we(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(),tb(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[r,a]=Il(t,n);this.setOutputMatrixTextureDriver(e,r,a)}setOutputMatrixWriteRegion(e,t,n,r){this.setOutputMatrixWriteRegionDriver(n,e,r,t)}setOutputPackedMatrixWriteRegion(e,t,n,r){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&ap(this.gl,this.program),ic(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),we(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),we(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=sc(this.gl,J().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(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.createQuery();return n.beginQuery(r.TIME_ELAPSED_EXT,a),a}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,r=this.getQueryTimerExtensionWebGL2(),a=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),a&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),r=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),r&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=Nz(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),sp(this.gl,e,this.framebuffer),this.debug&&ic(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(sp(this.gl,this.outputTexture,this.framebuffer),this.debug&&ic(this.gl)):jm(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;sp(r,e,this.framebuffer),this.debug&&ic(r),this.outputTexture=e,we(r,()=>r.viewport(0,0,t,n)),we(r,()=>r.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,r){this.throwIfDisposed(),we(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 Nz(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:Cb}=R;function Dz(e,t,n,r){let a=[];e.forEach(p=>{let f=v.sizeFromShape(p.shapeInfo.logicalShape);p.shapeInfo.isUniform?a.push(`uniform float ${p.name}${f>1?`[${f}]`:""};`):(a.push(`uniform sampler2D ${p.name};`),a.push(`uniform int offset${p.name};`))});let s=a.join(`
+`),i=e.map(p=>Sz(p,t,r)).join(`
+`),o=t.texShape,l=fn(),c=Ez(l),u,h,d=Fz(l);return t.isPacked?(u=Tz(t.logicalShape,o),h=Mz(l)):(u=Cz(t.logicalShape,o),h=Rz(l)),r&&(d+=$z),[d,c,h,s,u,i,n].join(`
+`)}function Nl(e){let t=e.shapeInfo.logicalShape;switch(t.length){case 0:return Oz(e);case 1:return zz(e);case 2:return Pz(e);case 3:return Lz(e);case 4:return Wz(e);case 5:return Bz(e);case 6:return Vz(e);default:throw new Error(`${t.length}-D input sampling is not yet supported`)}}function Eb(e){switch(e.shapeInfo.logicalShape.length){case 0:return Uz(e);case 1:return jz(e);case 2:return Hz(e);case 3:return Gz(e);default:return qz(e)}}function Sz(e,t,n=!1){let r="";n?r+=Eb(e):r+=Nl(e);let a=e.shapeInfo.logicalShape,s=t.logicalShape;return a.length<=s.length&&(n?r+=Xz(e,t):r+=Kz(e,t)),r}function Tz(e,t){switch(e.length){case 0:return Rb();case 1:return Zz(e,t);case 2:return Qz(e,t);case 3:return Yz(e,t);default:return Jz(e,t)}}function Cz(e,t){switch(e.length){case 0:return Rb();case 1:return eP(e,t);case 2:return sP(e,t);case 3:return tP(e,t);case 4:return nP(e,t);case 5:return rP(e,t);case 6:return aP(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function Ez(e){return`
     float sampleTexture(sampler2D textureSampler, vec2 uv) {
       return ${e.texture2D}(textureSampler, uv).r;
     }
-  `}function Lz(e){return`
+  `}function Rz(e){return`
     void setOutput(float val) {
       ${e.output} = vec4(val, 0, 0, 0);
     }
-  `}function Wz(e){return`
+  `}function Mz(e){return`
     void setOutput(vec4 val) {
       ${e.output} = val;
     }
-  `}function Bz(e){return`${e.version}
+  `}function Fz(e){return`${e.version}
     precision highp float;
     precision highp int;
     precision highp sampler2D;
@@ -327,10 +327,10 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       return fract((p3.x + p3.y) * p3.z);
     }
 
-    ${fP}
-    ${mP}
-    ${AP}
-  `}var fP=`
+    ${iP}
+    ${oP}
+    ${lP}
+  `}var iP=`
 vec2 uvFromFlat(int texNumR, int texNumC, int index) {
   int texR = index / texNumC;
   int texC = index - texR * texNumC;
@@ -342,7 +342,7 @@ vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,mP=`
+`,oP=`
 vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texNumC, int row, int col) {
   int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
@@ -350,7 +350,7 @@ vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,AP=`
+`,lP=`
 vec2 packedUVfrom3D(int texNumR, int texNumC,
     int texelsInBatch, int texelsInLogicalRow, int b,
     int row, int col) {
@@ -359,7 +359,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   int texC = index - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,Vz=`
+`,$z=`
   float getChannel(vec4 frag, vec2 innerDims) {
     vec2 modCoord = mod(innerDims, 2.);
     return modCoord.x == 0. ?
@@ -370,11 +370,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     float modCoord = mod(float(dim), 2.);
     return modCoord == 0. ? frag.r : frag.g;
   }
-`;function E_(){return`
+`;function Rb(){return`
     int getOutputCoords() {
       return 0;
     }
-  `}function aP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?`
+  `}function Zz(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 * ${n[1]}.0);
       }
@@ -388,7 +388,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${n[0]}, ${n[1]}));
       return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
     }
-  `}function lP(e,t){return t[0]===1?`
+  `}function eP(e,t){return t[0]===1?`
       int getOutputCoords() {
         return int(resultUV.x * ${t[1]}.0);
       }
@@ -402,7 +402,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${t[0]}, ${t[1]}));
       return resTexRC.x * ${t[1]} + resTexRC.y;
     }
-  `}function sP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
+  `}function Yz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${n[0]}, ${n[1]}));
@@ -416,7 +416,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec3(b, r, c);
     }
-  `}function uP(e,t){let n=_i(["r","c","d"],e);return`
+  `}function tP(e,t){let n=bi(["r","c","d"],e);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${t[0]}, ${t[1]}));
@@ -424,7 +424,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec3(r, c, d);
     }
-  `}function iP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
+  `}function Jz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),s=a,i="",o="b, r, c";for(let l=2;l<e.length-1;l++)s*=e[e.length-l-1],i=`
       int b${l} = index / ${s};
       index -= b${l} * ${s};
     `+i,o=`b${l}, `+o;return`
@@ -443,7 +443,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec${e.length}(${o});
     }
-  `}function cP(e,t){let n=_i(["r","c","d","d2"],e);return`
+  `}function nP(e,t){let n=bi(["r","c","d","d2"],e);return`
     ivec4 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -451,7 +451,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${n}
       return ivec4(r, c, d, d2);
     }
-  `}function hP(e,t){let n=_i(["r","c","d","d2","d3"],e);return`
+  `}function rP(e,t){let n=bi(["r","c","d","d2","d3"],e);return`
     ivec5 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                              ${t[1]}));
@@ -463,7 +463,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec5 outShape = ivec5(r, c, d, d2, d3);
       return outShape;
     }
-  `}function dP(e,t){let n=_i(["r","c","d","d2","d3","d4"],e);return`
+  `}function aP(e,t){let n=bi(["r","c","d","d2","d3","d4"],e);return`
     ivec6 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -474,7 +474,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec6 result = ivec6(r, c, d, d2, d3, d4);
       return result;
     }
-  `}function oP(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
+  `}function Qz(e,t){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return`
       ivec2 getOutputCoords() {
         return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
       }
@@ -489,7 +489,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       return ivec2(r, c);
     }
-  `}function pP(e,t){return v.arraysEqual(e,t)?`
+  `}function sP(e,t){return v.arraysEqual(e,t)?`
       ivec2 getOutputCoords() {
         return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
       }
@@ -516,26 +516,26 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       int c = index - r * ${e[1]};
       return ivec2(r, c);
     }
-  `}function bi(e){return`offset${e}`}function Yz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=fn();return`
+  `}function _i(e){return`offset${e}`}function Uz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=fn();return`
     vec4 ${n}() {
       return ${r.texture2D}(${t}, halfCR);
     }
-  `}function jz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
+  `}function Oz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${t};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
       float ${n}() {
         return sampleTexture(${t}, halfCR);
       }
-    `;let[s,i]=e.shapeInfo.texShape,o=bi(t);return`
+    `;let[s,i]=e.shapeInfo.texShape,o=_i(t);return`
     float ${n}() {
       vec2 uv = uvFromFlat(${s}, ${i}, ${o});
       return sampleTexture(${t}, uv);
     }
-  `}function Jz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=fn();return`
+  `}function jz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),r=e.shapeInfo.texShape,a=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)],s=fn();return`
     vec4 ${n}(int index) {
       vec2 uv = packedUVfrom1D(
         ${a[0]}, ${a[1]}, index);
       return ${s.texture2D}(${t}, uv);
     }
-  `}function Hz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
+  `}function zz(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);if(e.shapeInfo.isUniform)return`
       float ${n}(int index) {
         ${Sl(e)}
       }
@@ -543,7 +543,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       float ${n}(int index) {
         return sampleTexture(${t}, halfCR);
       }
-    `;let i=bi(t);return s===1?`
+    `;let i=_i(t);return s===1?`
       float ${n}(int index) {
         vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / ${a}.0);
         return sampleTexture(${t}, uv);
@@ -558,24 +558,24 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${a}, ${s}, index + ${i});
       return sampleTexture(${t}, uv);
     }
-  `}function Qz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=fn();if(a!=null&&v.arraysEqual(t,a))return`
+  `}function Hz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=a[0],i=a[1],o=fn();if(a!=null&&v.arraysEqual(t,a))return`
       vec4 ${r}(int row, int col) {
         vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${s}.0);
 
         return ${o.texture2D}(${n}, uv);
       }
-    `;let l=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],u=Math.ceil(t[1]/2);return`
+    `;let l=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],c=Math.ceil(t[1]/2);return`
     vec4 ${r}(int row, int col) {
-      vec2 uv = packedUVfrom2D(${u}, ${l[0]}, ${l[1]}, row, col);
+      vec2 uv = packedUVfrom2D(${c}, ${l[0]}, ${l[1]}, row, col);
       return ${o.texture2D}(${n}, uv);
     }
-  `}function Gz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
+  `}function Pz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape;if(a!=null&&v.arraysEqual(t,a)){let h=a[0],d=a[1];return`
     float ${r}(int row, int col) {
       vec2 uv = (vec2(col, row) + halfCR) / vec2(${d}.0, ${h}.0);
       return sampleTexture(${n}, uv);
     }
   `}let{newShape:s,keptDims:i}=v.squeezeShape(t),o=s;if(o.length<t.length){let h=Tl(e,o),d=["row","col"];return`
-      ${Il(h)}
+      ${Nl(h)}
       float ${r}(int row, int col) {
         return ${r}(${Cl(d,i)});
       }
@@ -584,38 +584,38 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         int index = round(dot(vec2(row, col), vec2(${t[1]}, 1)));
         ${Sl(e)}
       }
-    `;let l=a[0],u=a[1],c=bi(n);return u===1?`
+    `;let l=a[0],c=a[1],u=_i(n);return c===1?`
     float ${r}(int row, int col) {
-      float index = dot(vec3(row, col, ${c}), vec3(${t[1]}, 1, 1));
+      float index = dot(vec3(row, col, ${u}), vec3(${t[1]}, 1, 1));
       vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
       return sampleTexture(${n}, uv);
     }
   `:l===1?`
     float ${r}(int row, int col) {
-      float index = dot(vec3(row, col, ${c}), vec3(${t[1]}, 1, 1));
-      vec2 uv = vec2((index + 0.5) / ${u}.0, 0.5);
+      float index = dot(vec3(row, col, ${u}), vec3(${t[1]}, 1, 1));
+      vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
       return sampleTexture(${n}, uv);
     }
   `:`
   float ${r}(int row, int col) {
     // Explicitly use integer operations as dot() only works on floats.
-    int index = row * ${t[1]} + col + ${c};
-    vec2 uv = uvFromFlat(${l}, ${u}, index);
+    int index = row * ${t[1]} + col + ${u};
+    vec2 uv = uvFromFlat(${l}, ${c}, index);
     return sampleTexture(${n}, uv);
   }
-`}function eP(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=Tl(e,h),f=["b","row","col"];return`
-        ${C_(p)}
+`}function Gz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=e.shapeInfo.texShape,s=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(t[0]===1){let h=t.slice(1),d=[1,2],p=Tl(e,h),f=["b","row","col"];return`
+        ${Eb(p)}
         vec4 ${r}(int b, int row, int col) {
           return ${r}(${Cl(f,d)});
         }
-      `}let i=s[0],o=s[1],l=Math.ceil(t[2]/2),u=l*Math.ceil(t[1]/2),c=fn();return`
+      `}let i=s[0],o=s[1],l=Math.ceil(t[2]/2),c=l*Math.ceil(t[1]/2),u=fn();return`
     vec4 ${r}(int b, int row, int col) {
       vec2 uv = packedUVfrom3D(
-        ${i}, ${o}, ${u}, ${l}, b, row, col);
-      return ${c.texture2D}(${n}, uv);
+        ${i}, ${o}, ${c}, ${l}, b, row, col);
+      return ${u.texture2D}(${n}, uv);
     }
-  `}function qz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=Tl(e,l),m=["row","col","depth"];return`
-        ${Il(f)}
+  `}function Lz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[1]*t[2],s=t[2],{newShape:i,keptDims:o}=v.squeezeShape(t),l=i;if(l.length<t.length){let f=Tl(e,l),m=["row","col","depth"];return`
+        ${Nl(f)}
         float ${r}(int row, int col, int depth) {
           return ${r}(${Cl(m,o)});
         }
@@ -625,29 +625,29 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                           vec3(${a}, ${s}, 1)));
         ${Sl(e)}
       }
-    `;let u=e.shapeInfo.texShape,c=u[0],h=u[1],d=e.shapeInfo.flatOffset;if(h===a&&d==null)return`
+    `;let c=e.shapeInfo.texShape,u=c[0],h=c[1],d=e.shapeInfo.flatOffset;if(h===a&&d==null)return`
         float ${r}(int row, int col, int depth) {
           float texR = float(row);
           float texC = dot(vec2(col, depth), vec2(${s}, 1));
           vec2 uv = (vec2(texC, texR) + halfCR) /
-                     vec2(${h}.0, ${c}.0);
+                     vec2(${h}.0, ${u}.0);
           return sampleTexture(${n}, uv);
         }
       `;if(h===s&&d==null)return`
     float ${r}(int row, int col, int depth) {
       float texR = dot(vec2(row, col), vec2(${t[1]}, 1));
       float texC = float(depth);
-      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${h}.0, ${c}.0);
+      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${h}.0, ${u}.0);
       return sampleTexture(${n}, uv);
     }
-  `;let p=bi(n);return`
+  `;let p=_i(n);return`
       float ${r}(int row, int col, int depth) {
         // Explicitly use integer operations as dot() only works on floats.
         int index = row * ${a} + col * ${s} + depth + ${p};
-        vec2 uv = uvFromFlat(${c}, ${h}, index);
+        vec2 uv = uvFromFlat(${u}, ${h}, index);
         return sampleTexture(${n}, uv);
       }
-  `}function tP(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],u=Math.ceil(t[n-1]/2),c=u*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,c*=t[n-f-1],d=`b${f} * ${c} + `+d;let p=fn();return`
+  `}function qz(e){let t=e.shapeInfo.logicalShape,n=t.length,r=e.name,a="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],o=i[0],l=i[1],c=Math.ceil(t[n-1]/2),u=c*Math.ceil(t[n-2]/2),h="int b, int row, int col",d=`b * ${u} + (row / 2) * ${c} + (col / 2)`;for(let f=2;f<n-1;f++)h=`int b${f}, `+h,u*=t[n-f-1],d=`b${f} * ${u} + `+d;let p=fn();return`
     vec4 ${a}(${h}) {
       int index = ${d};
       int texR = index / ${l};
@@ -655,8 +655,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${o});
       return ${p.texture2D}(${r}, uv);
     }
-  `}function Xz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=Tl(e,o),m=["row","col","depth","depth2"];return`
-      ${Il(f)}
+  `}function Wz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[3],s=t[2]*a,i=t[1]*s,{newShape:o,keptDims:l}=v.squeezeShape(t);if(o.length<t.length){let f=Tl(e,o),m=["row","col","depth","depth2"];return`
+      ${Nl(f)}
       float ${r}(int row, int col, int depth, int depth2) {
         return ${r}(${Cl(m,l)});
       }
@@ -666,7 +666,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                           vec4(${i}, ${s}, ${a}, 1)));
         ${Sl(e)}
       }
-    `;let u=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,h=c[0],d=c[1];if(d===i&&u==null)return`
+    `;let c=e.shapeInfo.flatOffset,u=e.shapeInfo.texShape,h=u[0],d=u[1];if(d===i&&c==null)return`
       float ${r}(int row, int col, int depth, int depth2) {
         float texR = float(row);
         float texC =
@@ -676,7 +676,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                    vec2(${d}.0, ${h}.0);
         return sampleTexture(${n}, uv);
       }
-    `;if(d===a&&u==null)return`
+    `;if(d===a&&c==null)return`
       float ${r}(int row, int col, int depth, int depth2) {
         float texR = dot(vec3(row, col, depth),
                          vec3(${t[1]*t[2]}, ${t[2]}, 1));
@@ -685,7 +685,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${d}.0, ${h}.0);
         return sampleTexture(${n}, uv);
       }
-    `;let p=bi(n);return`
+    `;let p=_i(n);return`
     float ${r}(int row, int col, int depth, int depth2) {
       // Explicitly use integer operations as dot() only works on floats.
       int index = row * ${i} + col * ${s} +
@@ -693,10 +693,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${h}, ${d}, index + ${p});
       return sampleTexture(${n}, uv);
     }
-  `}function Kz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let m=Tl(e,l),A=["row","col","depth","depth2","depth3"];return`
-      ${Il(m)}
+  `}function Bz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:c}=v.squeezeShape(t);if(l.length<t.length){let m=Tl(e,l),A=["row","col","depth","depth2","depth3"];return`
+      ${Nl(m)}
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
-        return ${r}(${Cl(A,u)});
+        return ${r}(${Cl(A,c)});
       }
     `}if(e.shapeInfo.isUniform)return`
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
@@ -706,7 +706,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           depth3;
         ${Sl(e)}
       }
-    `;let c=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,d=h[0],p=h[1];if(p===o&&c==null)return`
+    `;let u=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,d=h[0],p=h[1];if(p===o&&u==null)return`
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
         int texR = row;
         float texC = dot(vec4(col, depth, depth2, depth3),
@@ -715,7 +715,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                    vec2(${p}.0, ${d}.0);
         return sampleTexture(${n}, uv);
       }
-    `;if(p===a&&c==null)return`
+    `;if(p===a&&u==null)return`
       float ${r}(int row, int col, int depth, int depth2, int depth3) {
         float texR = dot(
           vec4(row, col, depth, depth2),
@@ -726,7 +726,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${p}.0, ${d}.0);
         return sampleTexture(${n}, uv);
       }
-    `;let f=bi(n);return`
+    `;let f=_i(n);return`
     float ${r}(int row, int col, int depth, int depth2, int depth3) {
       // Explicitly use integer operations as dot() only works on floats.
       int index = row * ${o} + col * ${i} + depth * ${s} +
@@ -734,29 +734,29 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${d}, ${p}, index);
       return sampleTexture(${n}, uv);
     }
-  `}function Zz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=Tl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
-      ${Il(A)}
+  `}function Vz(e){let t=e.shapeInfo.logicalShape,n=e.name,r="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let A=Tl(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
+      ${Nl(A)}
       float ${r}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
         return ${r}(${Cl(y,s)});
       }
-    `}let i=t[5],o=t[4]*i,l=t[3]*o,u=t[2]*l,c=t[1]*u;if(e.shapeInfo.isUniform)return`
+    `}let i=t[5],o=t[4]*i,l=t[3]*o,c=t[2]*l,u=t[1]*c;if(e.shapeInfo.isUniform)return`
       float ${r}(int row, int col, int depth,
                   int depth2, int depth3, int depth4) {
         int index = round(dot(
           vec4(row, col, depth, depth2),
-          vec4(${c}, ${u}, ${l}, ${o})) +
+          vec4(${u}, ${c}, ${l}, ${o})) +
           dot(
             vec2(depth3, depth4),
             vec2(${i}, 1)));
         ${Sl(e)}
       }
-    `;let h=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,p=d[0],f=d[1];if(f===c&&h==null)return`
+    `;let h=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,p=d[0],f=d[1];if(f===u&&h==null)return`
       float ${r}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
         int texR = row;
         float texC = dot(vec4(col, depth, depth2, depth3),
-          vec4(${u}, ${l}, ${o}, ${i})) +
+          vec4(${c}, ${l}, ${o}, ${i})) +
                float(depth4);
         vec2 uv = (vec2(texC, texR) + halfCR) /
                    vec2(${f}.0, ${p}.0);
@@ -775,11 +775,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${f}.0, ${p}.0);
         return sampleTexture(${n}, uv);
       }
-    `;let m=bi(n);return`
+    `;let m=_i(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} +
+      int index = row * ${u} + col * ${c} + depth * ${l} +
           depth2 * ${o} + depth3 * ${i} + depth4 + ${m};
       vec2 uv = uvFromFlat(${p}, ${f}, index);
       return sampleTexture(${n}, uv);
@@ -790,8 +790,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         return ${t}[i];
       }
     }
-  `}function nP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=T_(e.shapeInfo.logicalShape,t.logicalShape),l=ct(i),u=i-s,c,h=["x","y","z","w","u","v"];s===0?c="":i<2&&o.length>=1?c="coords = 0;":c=o.map(A=>`coords.${h[A+u]} = 0;`).join(`
-`);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((A,y)=>`coords.${h[y+u]}`).join(", ");let p="return outputValue;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)p=`
+  `}function Xz(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=Cb(e.shapeInfo.logicalShape,t.logicalShape),l=ut(i),c=i-s,u,h=["x","y","z","w","u","v"];s===0?u="":i<2&&o.length>=1?u="coords = 0;":u=o.map(A=>`coords.${h[A+c]} = 0;`).join(`
+`);let d="";i<2&&s>0?d="coords":d=e.shapeInfo.logicalShape.map((A,y)=>`coords.${h[y+c]}`).join(", ");let p="return outputValue;",f=v.sizeFromShape(e.shapeInfo.logicalShape)===1,m=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!f&&!m)p=`
       return vec4(outputValue.xy, outputValue.xy);
     `;else if(f&&!m)i===1?p=`
         return vec4(outputValue.x, outputValue.x, 0., 0.);
@@ -800,26 +800,26 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       `;else if(o.length){let A=s-2,y=s-1;o.indexOf(A)>-1&&o.indexOf(y)>-1?p="return vec4(outputValue.x);":o.indexOf(A)>-1?p="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(y)>-1&&(p="return vec4(outputValue.xx, outputValue.zz);")}return`
     vec4 ${a}() {
       ${l} coords = getOutputCoords();
-      ${c}
+      ${u}
       vec4 outputValue = get${r}(${d});
       ${p}
     }
-  `}function rP(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
+  `}function Kz(e,t){let n=e.name,r=n.charAt(0).toUpperCase()+n.slice(1),a="get"+r+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
       float ${a}() {
         return sampleTexture(${n}, resultUV);
       }
-    `;let u=ct(l),c=T_(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&c.length>=1?d="coords = 0;":d=c.map(m=>`coords.${p[m+h]} = 0;`).join(`
+    `;let c=ut(l),u=Cb(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,d,p=["x","y","z","w","u","v"];o===0?d="":l<2&&u.length>=1?d="coords = 0;":d=u.map(m=>`coords.${p[m+h]} = 0;`).join(`
 `);let f="";return l<2&&o>0?f="coords":f=e.shapeInfo.logicalShape.map((m,A)=>`coords.${p[A+h]}`).join(", "),`
     float ${a}() {
-      ${u} coords = getOutputCoords();
+      ${c} coords = getOutputCoords();
       ${d}
       return get${r}(${f});
     }
-  `}function ct(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Tl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function Cl(e,t){return t.map(n=>e[n]).join(", ")}function yP(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=Uz(s,o,a,t.packedInputs),u=e.createProgram(l),c=null,h=e.getUniformLocation(u,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(c=e.getUniformLocation(u,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(u,f,m),d[`offset${f}`]=e.getUniformLocation(u,`offset${f}`,m)}return{program:t,source:l,webGLProgram:u,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:c,nanLoc:h}}function R_(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function gP(e,t,n,r,a){R_(t.inShapeInfos,n),R_([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let u=t.program.variableNames[l],c=t.uniformLocations[u],h=t.uniformLocations[`offset${u}`];if(c!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(c,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(c,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,c,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function xP(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:wP,bincountImpl:F_,bincountReduceImpl:_P,ceilImpl:bP,concatImpl:vP,expImpl:kP,expm1Impl:NP,floorImpl:IP,gatherV2Impl:SP,greaterImpl:TP,lessImpl:CP,linSpaceImpl:EP,logImpl:RP,maxImpl:FP,maximumImpl:MP,minimumImpl:$P,multiplyImpl:DP,negImpl:OP,prodImpl:zP,rangeImpl:PP,rsqrtImpl:LP,simpleAbsImpl:M_,sliceImpl:WP,stridedSliceImpl:BP,subImpl:VP,tileImpl:UP,topKImpl:jP,transposeImpl:tA,uniqueImpl:HP}=Tm;function $_(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function mn(e,t){return t===1?[e]:$_(e,t)}function GP(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var ZP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
+  `}function ut(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Tl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function Cl(e,t){return t.map(n=>e[n]).join(", ")}function uP(e,t,n,r){let a=t.userCode,s=n.map((p,f)=>{let m={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(m.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[f],shapeInfo:m}}),i=s.map(p=>p.shapeInfo),o={logicalShape:r.shape,texShape:r.texData.texShape,isUniform:!1,isPacked:r.texData.isPacked,flatOffset:null},l=Dz(s,o,a,t.packedInputs),c=e.createProgram(l),u=null,h=e.getUniformLocation(c,"NAN",!1);J().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(c,"INFINITY",!1));let d={};for(let p=0;p<t.variableNames.length;p++){let f=t.variableNames[p],m=!1;d[f]=e.getUniformLocation(c,f,m),d[`offset${f}`]=e.getUniformLocation(c,`offset${f}`,m)}return{program:t,source:l,webGLProgram:c,uniformLocations:d,inShapeInfos:i,outShapeInfo:o,infLoc:u,nanLoc:h}}function Mb(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,r)=>{let a=n.logicalShape,s=t[r],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function cP(e,t,n,r,a){Mb(t.inShapeInfos,n),Mb([t.outShapeInfo],[r]);let s=r.texData.texture,i=r.texData.texShape;r.texData.isPacked?e.setOutputPackedMatrixTexture(s,i[0],i[1]):e.setOutputMatrixTexture(s,i[0],i[1]),e.setProgram(t.webGLProgram),J().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,Infinity),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((o,l)=>{let c=t.program.variableNames[l],u=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`];if(u!=null){if(o.isUniform){if(v.sizeFromShape(o.shape)<2)e.gl.uniform1f(u,o.uniformValues[0]);else{let d=o.uniformValues;d instanceof Float32Array||(d=new Float32Array(d)),e.gl.uniform1fv(u,d)}return}o.texData.slice!=null&&h!=null&&e.gl.uniform1i(h,o.texData.slice.flatOffset),e.setInputMatrixTexture(o.texData.texture,u,l)}}),a!=null&&a(e,t.webGLProgram),e.executeProgram()}function hP(e,t,n){let r="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0,l=i.isUniform?"uniform":i.texData.texShape;r+=`${i.shape}_${l}_${o}`});let a=e.userCode,s=e.constructor.name;return s+="_"+r+"_"+a,s}var{addImpl:dP,bincountImpl:Fb,bincountReduceImpl:pP,ceilImpl:fP,concatImpl:mP,expImpl:AP,expm1Impl:yP,floorImpl:gP,gatherV2Impl:xP,greaterImpl:wP,lessImpl:bP,linSpaceImpl:_P,logImpl:vP,maxImpl:kP,maximumImpl:IP,minimumImpl:NP,multiplyImpl:SP,negImpl:TP,prodImpl:CP,rangeImpl:EP,rsqrtImpl:RP,simpleAbsImpl:$b,sliceImpl:MP,stridedSliceImpl:FP,subImpl:$P,tileImpl:DP,topKImpl:OP,transposeImpl:tA,uniqueImpl:zP}=Tm;function Db(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function mn(e,t){return t===1?[e]:Db(e,t)}function PP(e,t){if(e===1)return"rc";let n="";for(let r=0;r<e;r++)n+=t[r],r<e-1&&(n+=",");return n}var VP=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
         void main() {
           setOutput(vec4(getA(), 0., 0., 0.));
         }
-      `;else{let n=mn("rc",t),r=ct(t),a=qP(t,e,n),s=XP(t,e[e.length-1],e[e.length-2],n),i=KP(e,n);this.userCode=`
+      `;else{let n=mn("rc",t),r=ut(t),a=LP(t,e,n),s=WP(t,e[e.length-1],e[e.length-2],n),i=BP(e,n);this.userCode=`
         void main() {
           ${r} rc = getOutputCoords();
 
@@ -831,7 +831,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             setOutput(vec4(${i}));
           }
         }
-      `}}};function YP(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function qP(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function XP(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
+      `}}};function UP(e,t){let n=[];for(let r=0;r<=1;r++)for(let a=0;a<=1;a++){let s=`${r===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let i=2;i<e;i++)s=`${t[t.length-1-i]},`+s;n.push(s)}return n}function LP(e,t,n){if(e===1)return`rc > ${t[0]}`;let r="";for(let a=e-2;a<e;a++)r+=`${n[a]} >= ${t[a]}`,a<e-1&&(r+="||");return r}function WP(e,t,n,r){if(e===1)return"";let a=r.slice(-2);return`
     int r = ${a[0]};
     int c = ${a[1]};
     int rp1 = r + 1;
@@ -839,12 +839,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
     bool cEdge = cp1 >= ${t};
     bool rEdge = rp1 >= ${n};
-  `}function KP(e,t){let n=e.length,r=YP(n,t);return n===1?`getA(rc),
+  `}function BP(e,t){let n=e.length,r=UP(n,t);return n===1?`getA(rc),
             rc + 1 >= ${e[0]} ? 0. : getA(rc + 1),
             0, 0`:`getA(${r[0]}),
           cEdge ? 0. : getA(${r[1]}),
           rEdge ? 0. : getA(${r[2]}),
-          rEdge || cEdge ? 0. : getA(${r[3]})`}var D_=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
+          rEdge || cEdge ? 0. : getA(${r[3]})`}var Ob=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let r=0;r<4;r++){let a="thisRC = rc;";r%2==1&&(a+="thisRC.z += 1;"),r>1&&(a+="thisRC.y += 1;"),n+=`
         ${a}
         ${r>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
           int flatIndex = getFlatIndex(thisRC);
@@ -856,7 +856,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
         ${r>0?"}":""}
       `}this.userCode=`
-      ${JP(t)}
+      ${jP(t)}
       ${Km(e)}
 
       void main() {
@@ -872,12 +872,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function JP(e){return`
+    `}};function jP(e){return`
     ivec3 inputCoordsFromReshapedOutCoords(int index) {
-      ${_i(["r","c","d"],e)}
+      ${bi(["r","c","d"],e)}
       return ivec3(r, c, d);
     }
-  `}var QP=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=z_(t,n),a=P_(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=O_(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===tn.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===tn.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===tn.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===tn.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===tn.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=z_(n,r),s=P_(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=O_(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function eL(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function O_(e,t,n,r,a){let s=tL(t,r),i;if(a){let[l,u]=Nl(e[0],e[1]);i=l*u}else{let[l,u]=lc(e[0],e[1]);i=l*u}let o=eL(n,s);return i*o}function tL(e,t){switch(e){case tn.PACKED_2X2_FLOAT32:return Qm(t);case tn.PACKED_2X2_FLOAT16:return eA(t);case tn.UNPACKED_FLOAT32:return Zm(t);case tn.UNPACKED_FLOAT16:return Ym(t);case tn.PACKED_4X1_UNSIGNED_BYTE:return Jm(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function nL(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?tn.PACKED_2X2_FLOAT32:tn.UNPACKED_FLOAT32:e?tn.PACKED_2X2_FLOAT16:tn.UNPACKED_FLOAT16}function z_(e,t){if(e===Jn.UPLOAD)return tn.PACKED_2X2_FLOAT32;if(e===Jn.RENDER||e==null)return nL(t);if(e===Jn.DOWNLOAD||e===Jn.PIXELS)return tn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function P_(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Va=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+  `}var HP=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let r=Pb(t,n),a=Lb(e,r,n);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=zb(e,r,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return r===tn.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):r===tn.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):r===tn.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):r===tn.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):r===tn.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,r){if(this.freeTextures==null)return;let a=Pb(n,r),s=Lb(t,a,r);s in this.freeTextures||(this.freeTextures[s]=[]);let i=zb(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,r),o=J().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],c=l.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function GP(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function zb(e,t,n,r,a){let s=qP(t,r),i;if(a){let[l,c]=Il(e[0],e[1]);i=l*c}else{let[l,c]=uc(e[0],e[1]);i=l*c}let o=GP(n,s);return i*o}function qP(e,t){switch(e){case tn.PACKED_2X2_FLOAT32:return Qm(t);case tn.PACKED_2X2_FLOAT16:return eA(t);case tn.UNPACKED_FLOAT32:return Zm(t);case tn.UNPACKED_FLOAT16:return Ym(t);case tn.PACKED_4X1_UNSIGNED_BYTE:return Jm(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function XP(e){return J().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?tn.PACKED_2X2_FLOAT32:tn.UNPACKED_FLOAT32:e?tn.PACKED_2X2_FLOAT16:tn.UNPACKED_FLOAT16}function Pb(e,t){if(e===Jn.UPLOAD)return tn.PACKED_2X2_FLOAT32;if(e===Jn.RENDER||e==null)return XP(t);if(e===Jn.DOWNLOAD||e===Jn.PIXELS)return tn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function Lb(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Va=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       float unaryOperation(float x) {
         ${t}
       }
@@ -888,11 +888,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},wr="if (isnan(x)) return x;",rL="return x;",L_="return abs(x);",aL="return (x >= 0.0) ? x : (exp(x) - 1.0);",sL=wr+`
+    `}},wr="if (isnan(x)) return x;",KP="return x;",Wb="return abs(x);",ZP="return (x >= 0.0) ? x : (exp(x) - 1.0);",YP=wr+`
   return (x < 0.0) ? 0.0 : x;
-`,iL=wr+`
+`,JP=wr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,hp="return x;",oL="return x;",lL=`
+`,dp="return x;",QP="return x;",eL=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -901,7 +901,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,uL=`
+`,tL=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -911,7 +911,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,cL=`
+`,nL=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -932,17 +932,17 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},hL=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=mn("rc",t),r=ct(t),a=GP(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
+    `}},rL=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=mn("rc",t),r=ut(t),a=PP(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
       void main() {
         ${r} rc = getOutputCoords();
         vec4 packedInput = getA(${a});
 
         setOutput(getChannel(packedInput, ${i}));
       }
-    `}},dL=Wr.whereImpl,pL=1e-7,fL=1e-4,nA={};function mL(e){return e in nA||(nA[e]={}),nA[e]}var AL=128,yL=600;function gL(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*yL/1024/1024}var Rl=class extends iu{constructor(e){super();if(this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Vr(J().getNumber("WEBGL_VERSION"));this.binaryCache=mL(J().getNumber("WEBGL_VERSION")),this.gpgpu=new cp(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new QP(this.gpgpu),this.numMBBeforeWarning=gL(),this.texData=new wh(this,$r())}nextDataId(){return Rl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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:Jn.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,a){if(J().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:Jn.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new El(i,hp):h=new Va(i,hp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let c;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);c=R.mergeRealAndImagArrays(h,d)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new El(r,hp):p=new Va(r,hp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let p=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...uc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];c=R.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}u!=null&&this.disposeIntermediateTensorInfo(u);let h=this.convertAndCacheOnCPU(e,c),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&$r().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return We(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Ww(n))throw J().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...uc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?sp(t):t,o=s?new Rz(i):new Ez(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture,u.texShape[0],u.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=$r().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=AL){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return dL(e.shape,t)}packedUnaryOp(e,t,n){let r=new El(e.shape,t),a=this.compileAndRun(r,[e],n);return $r().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=M_(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,L_,e.dtype);let t=new Va(e.shape,L_),n=this.compileAndRun(t,[e]);return $r().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return $r().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new hL(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new ZP(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[gi(e.shape),...xi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[gi(t),...xi(t)],s=new D_(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=sp(r),i;n?i=new Cz(s):i=new Tz(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===oc.DENSE){let m=uc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!ic(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let u={shape:s.shape,texData:i,isUniform:!1},c=xP(e,l,u),h=this.getAndSaveBinary(c,()=>yP(this.gpgpu,e,l,u)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),gP(this.gpgpu,h,l,u,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=W(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(ve(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?pL:fL}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let c=t.texShape;if(c==null&&(c=n_(n,o),t.texShape=c),a!=null){let h=sp(n),d,p=c[1],f=c[0],m=a instanceof Uint8Array;o?([p,f]=Nl(c[0],c[1]),d=new Mz(h,[f,p],m)):d=new Fz(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Jn.PIXELS:this.texData.get(A.dataId).usage=Jn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-u)}else{let h=this.acquireTexture(c,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=xL(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Rl.nextDataId=0;function xL(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 ${t}`)}var W_="3.3.0";function B_(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}$u.isBrowser()&&il("webgl",()=>new Rl,2);var wL={forceHalfFloat:B_},V_=`
+    `}},aL=Wr.whereImpl,sL=1e-7,iL=1e-4,nA={};function oL(e){return e in nA||(nA[e]={}),nA[e]}var lL=128,uL=600;function cL(){return J().global.screen==null?1024:J().global.screen.height*J().global.screen.width*window.devicePixelRatio*uL/1024/1024}var Rl=class extends ou{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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!J().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Vr(J().getNumber("WEBGL_VERSION"));this.binaryCache=oL(J().getNumber("WEBGL_VERSION")),this.gpgpu=new hp(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 HP(this.gpgpu),this.numMBBeforeWarning=cL(),this.texData=new bh(this,$r())}nextDataId(){return Rl.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((J().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||J().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:Jn.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,a){if(J().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:Jn.UPLOAD,refCount:a})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:r,complexTensorInfos:a,slice:s,shape:i,isPacked:o}=t;if(s!=null){let h;o?h=new El(i,dp):h=new Va(i,dp);let d=this.runWebGLProgram(h,[{dataId:e,shape:i,dtype:r}],r),p=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(r==="string")return n;let l=this.activeTimers!=null,c;l&&(c=v.now());let u;if(r==="complex64"){let h=this.readSync(a.real.dataId),d=this.readSync(a.imag.dataId);u=R.mergeRealAndImagArrays(h,d)}else u=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-c),this.convertAndCacheOnCPU(e,u)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(f=>p.push(f))}let t=this.texData.get(e),{values:n,shape:r,slice:a,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(a!=null){let p;o?p=new El(r,dp):p=new Va(r,dp);let f=this.runWebGLProgram(p,[{dataId:e,shape:r,dtype:s}],s),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(!J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&J().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,c;if(s!=="complex64"&&J().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let p=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...cc(r))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let u;if(s==="complex64"){let p=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),f=p[0],m=p[1];u=R.mergeRealAndImagArrays(f,m)}else if(l==null)u=this.getValuesFromTexture(e);else{let p=v.sizeFromShape(r);u=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}c!=null&&this.disposeIntermediateTensorInfo(c);let h=this.convertAndCacheOnCPU(e,u),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(p=>p(h)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&$r().removeDataId(e,this),this.pendingDeletes--),h}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(r=>v.decodeString(r))}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return We(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Bw(n))throw J().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:r}=this.texData.get(e),a=v.sizeFromShape(t);if(J().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),d=this.texData.get(h.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(d.texture,...cc(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),p}let s=J().getBool("WEBGL_PACK")&&r===!0,i=s?ip(t):t,o=s?new vz(i):new _z(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),c=this.texData.get(l.dataId),u=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),u}timerAvailable(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],r=!1;this.programTimersStack==null?(this.programTimersStack=n,r=!0):this.activeTimers.push(n),this.activeTimers=n,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,r&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,c)=>({name:s[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(J().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:r,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(r,n),this.textureManager.releaseTexture(t,r,a,s)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return J().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=$r().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=lL){let n=this.getCPUBackend();return!J().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){R.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return aL(e.shape,t)}packedUnaryOp(e,t,n){let r=new El(e.shape,t),a=this.compileAndRun(r,[e],n);return $r().makeTensorFromDataId(a.dataId,a.shape,a.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let r=$b(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,r)}if(J().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,Wb,e.dtype);let t=new Va(e.shape,Wb),n=this.compileAndRun(t,[e]);return $r().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let r;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let a=n.map(s=>v.encodeString(s));r=this.write(a,e,t)}else r=this.write(n,e,t);return this.texData.get(r).usage=null,{dataId:r,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:r}=this.makeTensorInfo(e,t,n);return $r().makeTensorFromDataId(r,e,t,this)}unpackTensor(e){let t=new rL(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new VP(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[gi(e.shape),...xi(e.shape)],r={dtype:e.dtype,shape:n,dataId:e.dataId},a=[gi(t),...xi(t)],s=new Ob(a,n),i=!0,o=this.runWebGLProgram(s,[r],e.dtype,null,i);return{dataId:o.dataId,shape:t,dtype:o.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:r,dtype:a}=t,s=ip(r),i;n?i=new bz(s):i=new wz(s);let o=!0,l=this.runWebGLProgram(i,[{shape:s,dtype:a,dataId:e}],a,null,o);return{dtype:a,shape:r,dataId:l.dataId}}runWebGLProgram(e,t,n,r,a=!1){let s=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(s.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===lc.DENSE){let m=cc(e.outputShape);i.texShape=m.map(A=>A*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(s.shape)===0)return i.values=v.getTypedArrayFromDType(s.dtype,0),s;let o=[],l=t.map(m=>{if(m.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(m.dataId);if(A.texture==null){if(!e.packedInputs&&v.sizeFromShape(m.shape)<=J().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:m.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=m.shape)}else if(!!A.isPacked!=!!e.packedInputs)m=A.isPacked?this.unpackTensor(m):this.packTensor(m),o.push(m),A=this.texData.get(m.dataId);else if(A.isPacked&&!oc(A.shape,m.shape)){let y=m,g=m.shape;m.shape=A.shape,m=this.packedReshape(m,g),o.push(m),A=this.texData.get(m.dataId),y.shape=g}return this.uploadToGPU(m.dataId),{shape:m.shape,texData:A,isUniform:!1}});this.uploadToGPU(s.dataId);let c={shape:s.shape,texData:i,isUniform:!1},u=hP(e,l,c),h=this.getAndSaveBinary(u,()=>uP(this.gpgpu,e,l,c)),d=this.activeTimers!=null,p;d&&(p=this.startTimer()),cP(this.gpgpu,h,l,c,r),o.forEach(m=>this.disposeIntermediateTensorInfo(m)),d&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let f=J().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let m=v.now();m-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=m)}if(!J().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&a===!1){let m=this.unpackTensor(s);return this.disposeIntermediateTensorInfo(s),m}return s}compileAndRun(e,t,n,r,a=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,r,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(J().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=L(()=>{if(!J().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=J().getBool("DEBUG");J().set("DEBUG",!1);let t=this.abs(ve(1e-8)).dataSync()[0];if(J().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?sL:iL}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:r,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,c;l&&(c=v.now());let u=t.texShape;if(u==null&&(u=rb(n,o),t.texShape=u),a!=null){let h=ip(n),d,p=u[1],f=u[0],m=a instanceof Uint8Array;o?([p,f]=Il(u[0],u[1]),d=new Iz(h,[f,p],m)):d=new kz(h,[f,p],m);let A=this.makeTensorInfo([f,p],r);m?this.texData.get(A.dataId).usage=Jn.PIXELS:this.texData.get(A.dataId).usage=Jn.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,f,a);let y=!0,g=this.runWebGLProgram(d,[A],r,null,y),w=this.texData.get(g.dataId);t.texture=w.texture,t.texShape=w.texShape,t.isPacked=w.isPacked,t.usage=w.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(g.dataId),t.values=null,l&&(this.uploadWaitMs+=v.now()-c)}else{let h=this.acquireTexture(u,i,r,o);t.texture=h}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:r}=n;return this.releaseGPUData(e),t!=null&&(n.values=hL(t,r)),n.values}acquireTexture(e,t,n,r){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,r)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}};Rl.nextDataId=0;function hL(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 Bb="3.3.0";function Vb(){J().set("WEBGL_FORCE_F16_TEXTURES",!0)}Du.isBrowser()&&il("webgl",()=>new Rl,2);var dL={forceHalfFloat:Vb},Ub=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,Fl=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
+`,Ml=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
       float binaryOperation(float a, float b) {
         ${e}
       }
@@ -952,17 +952,17 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float b = getBAtOutCoords();
         setOutput(binaryOperation(a, b));
       }
-    `}},dp=`
+    `}},pp=`
   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;
-`,hc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=R.assertAndGetBroadcastShape(t,n);let a=this.outputShape.length,s="";if(r)if(a===0||v.sizeFromShape(this.outputShape)===1)s=`
+`,dc=class{constructor(e,t,n,r=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=R.assertAndGetBroadcastShape(t,n);let a=this.outputShape.length,s="";if(r)if(a===0||v.sizeFromShape(this.outputShape)===1)s=`
           result.y = 0.;
           result.z = 0.;
           result.w = 0.;
         `;else if(s=`
-          ${ct(a)} coords = getOutputCoords();
+          ${ut(a)} coords = getOutputCoords();
         `,a===1)s+=`
             result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
             result.z = 0.;
@@ -989,21 +989,21 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function zn(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 _L={kernelName:Ns,backendName:"webgl",kernelFunc:zn};function Ua(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=zn({inputs:{x:r},backend:n}),l=zn({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var bL={kernelName:Ch,backendName:"webgl",kernelFunc:Ua},U_="return (a < 0.) ? b * a : a;",j_=`
+    `}};function zn(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 pL={kernelName:Is,backendName:"webgl",kernelFunc:zn};function Ua(e){let{inputs:t,backend:n}=e,{real:r,imag:a}=t,s=n.makeTensorInfo(r.shape,"complex64"),i=n.texData.get(s.dataId),o=zn({inputs:{x:r},backend:n}),l=zn({inputs:{x:a},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var fL={kernelName:Eh,backendName:"webgl",kernelFunc:Ua},jb="return (a < 0.) ? b * a : a;",Hb=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function vL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hc(j_,a.shape,i.shape):new Fl(U_,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var kL={kernelName:Is,backendName:"webgl",kernelFunc:vL},H_="return (a < 0.) ? b * a : a;",G_=`
+`;function mL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{alpha:s}=r,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new dc(Hb,a.shape,i.shape):new Ml(jb,a.shape,i.shape),l=n.runWebGLProgram(o,[a,i],a.dtype);return n.disposeIntermediateTensorInfo(i),l}var AL={kernelName:Ns,backendName:"webgl",kernelFunc:mL},Gb="return (a < 0.) ? b * a : a;",qb=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function NL(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hc(G_,r.shape,a.shape):new Fl(H_,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var IL={kernelName:Ps,backendName:"webgl",kernelFunc:NL},q_="if (isnan(x)) return x;",SL=`
+`;function yL(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new dc(qb,r.shape,a.shape):new Ml(Gb,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)}var gL={kernelName:Ps,backendName:"webgl",kernelFunc:yL},Xb="if (isnan(x)) return x;",xL=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,TL=`
+`,wL=`
   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 Ze({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let u=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new El(i.shape,t):c=new Va(i.shape,e),o.runWebGLProgram(c,[i],l)}}function nn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,c=o;if(r&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[b,_]=w,x={dataId:b.dataId,dtype:b.dtype,shape:l.shape},I={dataId:_.dataId,dtype:_.dtype,shape:u.shape},S=new Fl(e,l.shape,u.shape);return c.runWebGLProgram(S,[x,I],ar(b.dtype,_.dtype))}),g=Ua({inputs:{real:A,imag:y},backend:c});return c.disposeIntermediateTensorInfo(A),c.disposeIntermediateTensorInfo(y),g}let h=s||ar(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&a!=null){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=a(l.shape,u.shape,f.values,m.values,h),g=c.makeTensorInfo(y,h),w=c.texData.get(g.dataId);return w.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new hc(t,l.shape,u.shape,n):p=new Fl(e,l.shape,u.shape),c.runWebGLProgram(p,[l,u],h)}}function pp(e,t=!1){if(e==="linear")return t?oL:rL;if(e==="relu")return t?uL:sL;if(e==="elu")return t?lL:aL;if(e==="relu6")return t?cL:iL;if(e==="prelu")return t?G_:H_;if(e==="leakyrelu")return t?j_:U_;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var X_=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let u=r?e[1]:e[2],c=Math.ceil(u/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
+`;function Ze({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let c=J().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,u;return c?u=new El(i.shape,t):u=new Va(i.shape,e),o.runWebGLProgram(u,[i],l)}}function nn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:c}=i,u=o;if(r&&l.dtype==="complex64"){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[b,_]=w,x={dataId:b.dataId,dtype:b.dtype,shape:l.shape},N={dataId:_.dataId,dtype:_.dtype,shape:c.shape},T=new Ml(e,l.shape,c.shape);return u.runWebGLProgram(T,[x,N],ar(b.dtype,_.dtype))}),g=Ua({inputs:{real:A,imag:y},backend:u});return u.disposeIntermediateTensorInfo(A),u.disposeIntermediateTensorInfo(y),g}let h=s||ar(l.dtype,c.dtype);if(u.shouldExecuteOnCPU([l,c])&&a!=null){let f=u.texData.get(l.dataId),m=u.texData.get(c.dataId),[A,y]=a(l.shape,c.shape,f.values,m.values,h),g=u.makeTensorInfo(y,h),w=u.texData.get(g.dataId);return w.values=A,g}let d=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new dc(t,l.shape,c.shape,n):p=new Ml(e,l.shape,c.shape),u.runWebGLProgram(p,[l,c],h)}}function fp(e,t=!1){if(e==="linear")return t?QP:KP;if(e==="relu")return t?tL:YP;if(e==="elu")return t?eL:ZP;if(e==="relu6")return t?nL:JP;if(e==="prelu")return t?qb:Gb;if(e==="leakyrelu")return t?Hb:jb;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var Kb=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let c=r?e[1]:e[2],u=Math.ceil(c/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${i}
         }`:l?m=`vec4 activation(vec4 a) {
@@ -1014,11 +1014,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",w="rc.x";e[0]<t[0]?g=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(w=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
       ${m}
 
-      const float sharedDimension = ${c}.0;
+      const float sharedDimension = ${u}.0;
 
       vec4 dot2x2ARowBCol(ivec3 rc) {
         vec4 result = vec4(0);
-        for (int i = 0; i < ${c}; i++) {
+        for (int i = 0; i < ${u}; i++) {
           int batchA = ${g};
           int batchB = ${w};
           vec4 a = getMatrixA(batchA, ${h});
@@ -1042,7 +1042,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}},K_={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Z_=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
+    `}},Zb={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Yb=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=R.assertAndGetBroadcastShape(t,n),this.userCode=`
       float binaryOpComplex(
           float areal, float aimag, float breal, float bimag) {
         ${e}
@@ -1055,7 +1055,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float bimag = getBImagAtOutCoords();
         setOutput(binaryOpComplex(areal, aimag, breal, bimag));
       }
-    `}},Y_="return a * b;";function J_(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),u=new Z_(K_.REAL,r.shape,a.shape),c=new Z_(K_.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Ua({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[u,c]=DP(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(c,s),d=n.texData.get(h.dataId);return d.values=u,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new hc(Y_,r.shape,a.shape):i=new Fl(Y_,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var CL={kernelName:$s,backendName:"webgl",kernelFunc:J_};function EL(e,t,n){let r=[gi(e.shape),...xi(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[gi(t),...xi(t)],i=new D_(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ye(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let c=i.texData.get(a.dataId);return c.isPacked&&!ic(a.shape,l)&&!(c.texture!==null&&ic(c.shape,l))?EL(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var RL={kernelName:Oo,backendName:"webgl",kernelFunc:ye},Q_=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${v.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";a%n>0&&(u=`
+    `}},Jb="return a * b;";function Qb(e){let{inputs:t,backend:n}=e,{a:r,b:a}=t,s=R.upcastType(r.dtype,a.dtype);if(r.dtype==="complex64"){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),c=new Yb(Zb.REAL,r.shape,a.shape),u=new Yb(Zb.IMAG,r.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:r.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:r.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Ua({inputs:{real:d,imag:p},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}if(n.shouldExecuteOnCPU([r,a])){let o=n.texData.get(r.dataId),l=n.texData.get(a.dataId),[c,u]=SP(r.shape,a.shape,o.values,l.values,s),h=n.makeTensorInfo(u,s),d=n.texData.get(h.dataId);return d.values=c,h}let i;return J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new dc(Jb,r.shape,a.shape):i=new Ml(Jb,r.shape,a.shape),n.runWebGLProgram(i,[r,a],s)}var bL={kernelName:$s,backendName:"webgl",kernelFunc:Qb};function _L(e,t,n){let r=[gi(e.shape),...xi(e.shape)],a={dtype:e.dtype,shape:r,dataId:e.dataId},s=[gi(t),...xi(t)],i=new Ob(s,r),o=!0,l=n.runWebGLProgram(i,[a],e.dtype,null,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ye(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{shape:s}=r,i=n,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),c=v.sizeFromShape(l);v.assert(o===c,()=>`The new shape (${l}) has ${c} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let u=i.texData.get(a.dataId);return u.isPacked&&!oc(a.shape,l)&&!(u.texture!==null&&oc(u.shape,l))?_L(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var vL={kernelName:Oo,backendName:"webgl",kernelFunc:ye},e_=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let u=1/t;l=`sumValue += dot(values * ${v.isInt(u)?u.toPrecision(2):u}, ones);`}let c="";a%n>0&&(c=`
         if (inIdx < 0 || inIdx >= ${a}) {
           return 0.0;
         }
@@ -1063,7 +1063,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
 
       float getValue(int batch, int inIdx) {
-        ${u}
+        ${c}
         return getX(batch, inIdx);
       }
 
@@ -1108,7 +1108,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(sumValue);
       }
-    `}},FL=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(n/4)*4,c=n%4,h=`
+    `}},kL=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:r,inSize:a,outSize:s}=e;this.outputShape=[r,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,u=n%4,h=`
       if (${t==="sum"}) {
         sumValue += dot(values, ones);
       } else if (${t==="prod"}) {
@@ -1150,7 +1150,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float allValue = 1.0;
         float anyValue = 0.0;
 
-        for (int i = 0; i < ${u}; i += 4) {
+        for (int i = 0; i < ${c}; i += 4) {
           int inIdx = inOffset + i;
           ${d} values = ${d}(
             getValue(batch, inIdx),
@@ -1162,8 +1162,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           ${h}
         }
 
-        int inIdx = inOffset + ${u};
-        if (${c===1}) {
+        int inIdx = inOffset + ${c};
+        if (${u===1}) {
           ${d} values = ${d}(
             getValue(batch, inIdx),
             initializationValue,
@@ -1172,7 +1172,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           );
 
           ${h}
-        } else if (${c===2}) {
+        } else if (${u===2}) {
           ${d} values = ${d}(
             getValue(batch, inIdx),
             getValue(batch, inIdx + 1),
@@ -1181,7 +1181,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           );
 
           ${h}
-        } else if (${c===3}) {
+        } else if (${u===3}) {
           ${d} values = ${d}(
             getValue(batch, inIdx),
             getValue(batch, inIdx + 1),
@@ -1193,12 +1193,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(${l});
       }
-    `}};function ML(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=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function vi(e,t,n,r){let a=ML(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:u}=a[i],c,h;n==="mean"?c=i===0?new Q_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new Q_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):c=new FL({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},n),h=s,s=r.runWebGLProgram(c,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var DL=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=ct(this.rank),a=$L(t);this.userCode=`
+    `}};function IL(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=R.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:r,outSize:Math.ceil(n/r)})}return t}function vi(e,t,n,r){let a=IL(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:c}=a[i],u,h;n==="mean"?u=i===0?new e_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},o):new e_({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c}):u=new kL({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:c},n),h=s,s=r.runWebGLProgram(u,[s],t),h.dataId!==e.dataId&&r.disposeIntermediateTensorInfo(h)}return s}var SL=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let r=ut(this.rank),a=NL(t);this.userCode=`
     void main() {
       ${r} resRC = getOutputCoords();
       setOutput(getA(${a}));
     }
-    `}};function $L(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var OL=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 ${this.rank} is not yet supported.`);let r=ct(this.rank),a=$_("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=a[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
+    `}};function NL(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],r=new Array(t);for(let a=0;a<e.length;a++)r[e[a]]=n[a];return r.join()}var TL=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let c=0;c<n.length;c++)n[c]=e[t[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let r=ut(this.rank),a=Db("rc",this.rank),s=new Array(this.rank);for(let c=0;c<t.length;c++)s[t[c]]=a[c];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
     void main() {
       ${r} rc = getOutputCoords();
       vec4 result = vec4(0.);
@@ -1215,14 +1215,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       }
       setOutput(result);
     }
-    `}};function fp(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new OL(e.shape,t):new DL(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function zL(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),u=l!=null,c=e;u&&(c=fp(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(c.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=ye({inputs:{x:c},attrs:{shape:[m,f]},backend:r}),y=id(e.dtype),g=vi(A,y,"sum",r),w=ye({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),u&&r.disposeIntermediateTensorInfo(c),w}function rA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return zL(a,s,i,n)}var PL={kernelName:Xs,backendName:"webgl",kernelFunc:rA};function In(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let c=0;c<l.length;c++)l[c]=a.shape[s[c]];let u;if(i.shouldExecuteOnCPU([a])){let c=i.texData.get(a.dataId).values,h=tA(c,a.shape,a.dtype,s,l);u=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(u.dataId);d.values=h}else u=fp(a,s,i);return u}var LL={kernelName:Qs,backendName:"webgl",kernelFunc:In},eb=1e3;function mp({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,h=n?e.shape[u-2]:e.shape[u-1],d=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),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(u>=2&&c>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let b=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],I=ye({inputs:{x:e},backend:a,attrs:{shape:_}}),S=ye({inputs:{x:t},backend:a,attrs:{shape:x}}),T=[I,S],M=Math.max(y,g),D=n?I.shape[1]:I.shape[2],z=s!=null,B=i!=null,U=l==="leakyrelu",j=l!=null?pp(l,!0):null,X=z||B||U||j!=null,H;if((p===1||f===1)&&D>eb&&X===!1){let Y=I,ae=S;n&&(Y=In({inputs:{x:I},backend:a,attrs:{perm:[0,2,1]}}),T.push(Y)),r&&(ae=In({inputs:{x:S},backend:a,attrs:{perm:[0,2,1]}}),T.push(ae));let te=f!==1,ie=f===1,Q=Y;te&&(Q=ye({inputs:{x:Y},backend:a,attrs:{shape:[M,D,1]}}),T.push(Q));let he=f===1?2:1,le=ae;ie&&(le=ye({inputs:{x:ae},backend:a,attrs:{shape:[M,1,D]}}),T.push(le));let fe=J_({inputs:{a:Q,b:le},backend:a});H=rA({inputs:{x:fe},backend:a,attrs:{axis:he,keepDims:!0}}),T.push(fe)}else{let Y=ar(e.dtype,t.dtype),ae=new X_(_,x,[M,p,f],n,r,z,j,B,U),te=[I,S];if(s!=null&&te.push(s),B&&te.push(i),U){let ie=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));te.push(ie),T.push(ie)}H=a.runWebGLProgram(ae,te,Y)}let ee=ye({inputs:{x:H},backend:a,attrs:{shape:b}});T.push(H);for(let Y of T)a.disposeIntermediateTensorInfo(Y);return ee}function WL(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:h}=r;return mp({a,b:s,transposeA:l,transposeB:u,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:c})}var BL={kernelName:ei,backendName:"webgl",kernelFunc:WL},tb="return abs(x);";function VL(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=M_(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new El(r.shape,tb):a=new Va(r.shape,tb),n.runWebGLProgram(a,[r],r.dtype)}var UL={kernelName:Yi,backendName:"webgl",kernelFunc:VL},jL=wr+`
+    `}};function mp(e,t,n){let r=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new TL(e.shape,t):new SL(e.shape,t);return n.runWebGLProgram(r,[e],e.dtype)}function CL(e,t,n,r){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=R.getAxesPermutation(o,s),c=l!=null,u=e;c&&(u=mp(e,l,r),o=R.getInnerMostAxes(o.length,s)),R.assertAxesAreInnerMostDims("sum",o,s);let[h,d]=R.computeOutAndReduceShapes(u.shape,o),p=h;n&&(p=R.expandShapeToKeepDim(h,i));let f=v.sizeFromShape(d),m=v.sizeFromShape(e.shape)/f,A=ye({inputs:{x:u},attrs:{shape:[m,f]},backend:r}),y=od(e.dtype),g=vi(A,y,"sum",r),w=ye({inputs:{x:g},attrs:{shape:p},backend:r});return r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(g),c&&r.disposeIntermediateTensorInfo(u),w}function rA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;return CL(a,s,i,n)}var EL={kernelName:Xs,backendName:"webgl",kernelFunc:rA};function Nn(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{perm:s}=r,i=n,o=a.shape.length,l=new Array(o);for(let u=0;u<l.length;u++)l[u]=a.shape[s[u]];let c;if(i.shouldExecuteOnCPU([a])){let u=i.texData.get(a.dataId).values,h=tA(u,a.shape,a.dtype,s,l);c=i.makeTensorInfo(l,a.dtype);let d=i.texData.get(c.dataId);d.values=h}else c=mp(a,s,i);return c}var RL={kernelName:Qs,backendName:"webgl",kernelFunc:Nn},t_=1e3;function Ap({a:e,b:t,transposeA:n,transposeB:r,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let c=e.shape.length,u=t.shape.length,h=n?e.shape[c-2]:e.shape[c-1],d=r?t.shape[u-1]:t.shape[u-2],p=n?e.shape[c-1]:e.shape[c-2],f=r?t.shape[u-2]:t.shape[u-1],m=e.shape.slice(0,-2),A=t.shape.slice(0,-2),y=v.sizeFromShape(m),g=v.sizeFromShape(A),w=y===g||y===1||g===1;v.assert(c>=2&&u>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${A}).`);let b=(y>g?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,f]);v.assert(h===d,()=>`Error in matMul: inner shapes (${h}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${r} must match.`);let _=n?[y,h,p]:[y,p,h],x=r?[g,f,d]:[g,d,f],N=ye({inputs:{x:e},backend:a,attrs:{shape:_}}),T=ye({inputs:{x:t},backend:a,attrs:{shape:x}}),C=[N,T],F=Math.max(y,g),z=n?N.shape[1]:N.shape[2],B=s!=null,V=i!=null,U=l==="leakyrelu",j=l!=null?fp(l,!0):null,X=B||V||U||j!=null,G;if((p===1||f===1)&&z>t_&&X===!1){let Y=N,ae=T;n&&(Y=Nn({inputs:{x:N},backend:a,attrs:{perm:[0,2,1]}}),C.push(Y)),r&&(ae=Nn({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),C.push(ae));let te=f!==1,oe=f===1,Q=Y;te&&(Q=ye({inputs:{x:Y},backend:a,attrs:{shape:[F,z,1]}}),C.push(Q));let he=f===1?2:1,le=ae;oe&&(le=ye({inputs:{x:ae},backend:a,attrs:{shape:[F,1,z]}}),C.push(le));let fe=Qb({inputs:{a:Q,b:le},backend:a});G=rA({inputs:{x:fe},backend:a,attrs:{axis:he,keepDims:!0}}),C.push(fe)}else{let Y=ar(e.dtype,t.dtype),ae=new Kb(_,x,[F,p,f],n,r,B,j,V,U),te=[N,T];if(s!=null&&te.push(s),V&&te.push(i),U){let oe=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));te.push(oe),C.push(oe)}G=a.runWebGLProgram(ae,te,Y)}let ee=ye({inputs:{x:G},backend:a,attrs:{shape:b}});C.push(G);for(let Y of C)a.disposeIntermediateTensorInfo(Y);return ee}function ML(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:c,activation:u,leakyreluAlpha:h}=r;return Ap({a,b:s,transposeA:l,transposeB:c,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:u})}var FL={kernelName:ei,backendName:"webgl",kernelFunc:ML},n_="return abs(x);";function $L(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])&&r.dtype!=="complex64"){let s=n.texData.get(r.dataId),i=$b(s.values);return n.makeTensorInfo(r.shape,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new El(r.shape,n_):a=new Va(r.shape,n_),n.runWebGLProgram(a,[r],r.dtype)}var DL={kernelName:Yi,backendName:"webgl",kernelFunc:$L},OL=wr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return acos(x);
-`,HL=Ze({opSnippet:jL}),GL={kernelName:Ji,backendName:"webgl",kernelFunc:HL},qL=wr+`
+`,zL=Ze({opSnippet:OL}),PL={kernelName:Ji,backendName:"webgl",kernelFunc:zL},LL=wr+`
   if (x < 1.0) return NAN;
-return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,backendName:"webgl",kernelFunc:XL},nb="return a + b;",ZL=nn({opSnippet:nb,packedOpSnippet:nb,supportsComplex:!0,cpuKernelImpl:wP}),YL={kernelName:Ia,backendName:"webgl",kernelFunc:ZL},JL=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+return log(x + sqrt(x * x - 1.0));`,WL=Ze({opSnippet:LL}),BL={kernelName:Qi,backendName:"webgl",kernelFunc:WL},r_="return a + b;",VL=nn({opSnippet:r_,packedOpSnippet:r_,supportsComplex:!0,cpuKernelImpl:dP}),UL={kernelName:Na,backendName:"webgl",kernelFunc:VL},jL=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1230,7 +1230,7 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
         float result = ${r};
         setOutput(result);
       }
-    `}},QL=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
+    `}},HL=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1238,7 +1238,7 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
         vec4 result = ${r};
         setOutput(result);
       }
-    `}};function Ap(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return zn({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=Ap({inputs:r.slice(0,o),backend:n}),u=Ap({inputs:r.slice(o),backend:n});return Ap({inputs:[l,u],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>ar(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new QL(r[0].shape,s):new JL(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var eW={kernelName:ls,backendName:"webgl",kernelFunc:Ap};function tW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("all",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var nW={kernelName:kh,backendName:"webgl",kernelFunc:tW};function rW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,o)),R.assertAxesAreInnerMostDims("any",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var aW={kernelName:Nh,backendName:"webgl",kernelFunc:rW},sW=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
+    `}};function yp(e){let{inputs:t,backend:n}=e,r=t;if(r.length===1)return zn({inputs:{x:r[0]},backend:n});if(r.length>J().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(r.length/2),l=yp({inputs:r.slice(0,o),backend:n}),c=yp({inputs:r.slice(o),backend:n});return yp({inputs:[l,c],backend:n})}let a=r.map(o=>o.dtype).reduce((o,l)=>ar(o,l)),s=r.map(o=>o.shape),i=J().getBool("WEBGL_PACK")?new HL(r[0].shape,s):new jL(r[0].shape,s);return n.runWebGLProgram(i,r,a)}var GL={kernelName:ls,backendName:"webgl",kernelFunc:yp};function qL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=Nn({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("all",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"all",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var XL={kernelName:Ih,backendName:"webgl",kernelFunc:qL};function KL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=Nn({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,o)),R.assertAxesAreInnerMostDims("any",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"any",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var ZL={kernelName:Nh,backendName:"webgl",kernelFunc:KL},YL=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:r,batchSize:a,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
@@ -1258,23 +1258,23 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
         }
         setOutput(float(bestIndex));
       }
-    `}},iW=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ct(o),u=mn("coords",o),c,h;if(s===1){h=o+1;let I=ct(h);c=`
-        ${I} sourceLocR = ${I}(${u.join()}, 0);
-        ++${u[o-1]};
-        ${I} sourceLocG = ${I}(${u.join()}, 0);
-        ++${u[o-2]};
-        ${I} sourceLocA = ${I}(${u.join()}, 0);
-        --${u[o-1]};
-        ${I} sourceLocB = ${I}(${u.join()}, 0);
-        --${u[o-2]};`}else h=o,c=`
+    `}},JL=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ut(o),c=mn("coords",o),u,h;if(s===1){h=o+1;let N=ut(h);u=`
+        ${N} sourceLocR = ${N}(${c.join()}, 0);
+        ++${c[o-1]};
+        ${N} sourceLocG = ${N}(${c.join()}, 0);
+        ++${c[o-2]};
+        ${N} sourceLocA = ${N}(${c.join()}, 0);
+        --${c[o-1]};
+        ${N} sourceLocB = ${N}(${c.join()}, 0);
+        --${c[o-2]};`}else h=o,u=`
         ${l} sourceLocR = coords;
-        ++${u[o-1]};
+        ++${c[o-1]};
         ${l} sourceLocG = coords;
-        ++${u[o-2]};
+        ++${c[o-2]};
         ${l} sourceLocA = coords;
-        --${u[o-1]};
+        --${c[o-1]};
         ${l} sourceLocB = coords;
-        --${u[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(I=>"int "+I),m=mn("sourceLocR",h-1).concat("inIdx.r"),A=mn("sourceLocG",h-1).concat("inIdx.g"),y=mn("sourceLocB",h-1).concat("inIdx.b"),g=mn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",b=r?"":`
+        --${c[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=mn("sourceLocR",h-1).concat("inIdx.r"),A=mn("sourceLocG",h-1).concat("inIdx.g"),y=mn("sourceLocB",h-1).concat("inIdx.b"),g=mn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",b=r?"":`
           inIdx = round(vec4(getBestIndicesAChannel(${m.join()}),
                              getBestIndicesAChannel(${A.join()}),
                              getBestIndicesAChannel(${y.join()}),
@@ -1294,9 +1294,9 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
       ${x}
       void main() {
         ${l} coords = getOutputCoords();
-        bool hasNextCol = ${u[o-1]} < ${i[o-1]-1};
-        bool hasNextRow = ${u[o-2]} < ${i[o-2]-1};
-        ${c}
+        bool hasNextCol = ${c[o-1]} < ${i[o-1]-1};
+        bool hasNextRow = ${c[o-2]} < ${i[o-2]-1};
+        ${u}
         ivec4 srcIdx = ivec4(sourceLocR${p}, sourceLocG${p},
           sourceLocB${p}, sourceLocA${p}) * ${t};
         ivec4 inIdx = srcIdx;
@@ -1320,23 +1320,23 @@ return log(x + sqrt(x * x - 1.0));`,XL=Ze({opSnippet:qL}),KL={kernelName:Qi,back
         }
         setOutput(bestIndex);
       }
-    `}};function rb(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new sW(o,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 h=rb(e,t,n,c);return e.disposeIntermediateTensorInfo(c),h}function ab(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new iW(a,i,n,r==null),l=r==null?[t]:[t,r],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let c=ab(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function sb(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),u=ye({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(u);let c=rb(e,u,r);s.push(c);let h=ye({inputs:{x:c},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return ab(e,t,r)}function oW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let c=sb(n,l,i[0],"max");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var lW={kernelName:us,backendName:"webgl",kernelFunc:oW};function uW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=In({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let c=sb(n,l,i[0],"min");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var cW={kernelName:uu,backendName:"webgl",kernelFunc:uW},hW=wr+`
+    `}};function a_(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=R.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new YL(o,n,r==null),c=[t];r!=null&&c.push(r);let u=e.runWebGLProgram(l,c,"int32");if(u.shape[1]===1)return u;let h=a_(e,t,n,u);return e.disposeIntermediateTensorInfo(u),h}function s_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=R.computeOptimalWindowSize(s),o=new JL(a,i,n,r==null),l=r==null?[t]:[t,r],c=e.runWebGLProgram(o,l,"int32");if(c.shape.length===t.shape.length){let u=s_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),u}return c}function i_(e,t,n,r){let a=[n];if(R.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!J().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=R.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),c=ye({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(c);let u=a_(e,c,r);s.push(u);let h=ye({inputs:{x:u},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return s_(e,t,r)}function QL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=Nn({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let u=i_(n,l,i[0],"max");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var eW={kernelName:us,backendName:"webgl",kernelFunc:QL};function tW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=R.getAxesPermutation(i,a.shape.length),l=a,c=[];o!=null&&(l=Nn({inputs:{x:a},backend:n,attrs:{perm:o}}),c.push(l),i=R.getInnerMostAxes(i.length,l.shape.length)),R.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let u=i_(n,l,i[0],"min");return c.forEach(h=>n.disposeIntermediateTensorInfo(h)),u}var nW={kernelName:cu,backendName:"webgl",kernelFunc:tW},rW=wr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return asin(x);
-`,dW=Ze({opSnippet:hW}),pW={kernelName:eo,backendName:"webgl",kernelFunc:dW},fW=wr+"return log(x + sqrt(x * x + 1.0));",mW=Ze({opSnippet:fW}),AW={kernelName:to,backendName:"webgl",kernelFunc:mW},yW=wr+`
+`,aW=Ze({opSnippet:rW}),sW={kernelName:eo,backendName:"webgl",kernelFunc:aW},iW=wr+"return log(x + sqrt(x * x + 1.0));",oW=Ze({opSnippet:iW}),lW={kernelName:to,backendName:"webgl",kernelFunc:oW},uW=wr+`
   return atan(x);
-`,gW=Ze({opSnippet:yW}),xW={kernelName:no,backendName:"webgl",kernelFunc:gW},wW=SL+`
+`,cW=Ze({opSnippet:uW}),hW={kernelName:no,backendName:"webgl",kernelFunc:cW},dW=xL+`
   return atan(a, b);
-`,_W=`
+`,pW=`
   vec4 result = atan(a, b);
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+TL+`
+  `+wL+`
   return result;
-`,bW=nn({opSnippet:wW,packedOpSnippet:_W}),vW={kernelName:ao,backendName:"webgl",kernelFunc:bW},kW=wr+`
+`,fW=nn({opSnippet:dW,packedOpSnippet:pW}),mW={kernelName:ao,backendName:"webgl",kernelFunc:fW},AW=wr+`
   if ((x < -1.0) || (x > 1.0)) return NAN;
-return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelName:ro,backendName:"webgl",kernelFunc:NW},dc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let I=">=";this.userCode=`
+return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,yW=Ze({opSnippet:AW}),gW={kernelName:ro,backendName:"webgl",kernelFunc:yW},pc=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=`
         const ivec2 strides = ivec2(${i}, ${o});
         const ivec2 pads = ivec2(${d}, ${p});
 
@@ -1356,7 +1356,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           int minMaxPosition = 0;
           float avgValue = 0.0;
 
-          for (int wR = 0; wR < ${c};
+          for (int wR = 0; wR < ${u};
               wR += ${l}) {
             int xR = xRCorner + wR;
 
@@ -1365,7 +1365,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             }
 
             for (int wC = 0; wC < ${h};
-                wC += ${u}) {
+                wC += ${c}) {
               int xC = xCCorner + wC;
 
               if (xC < 0 || xC >= ${e.inWidth}) {
@@ -1378,7 +1378,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
               // use the current value.
               float currMinMaxValue = mix(
                   value, minMaxValue, minMaxValueFound);
-              if (value ${I} currMinMaxValue) {
+              if (value ${N} currMinMaxValue) {
                 minMaxValue = value;
                 minMaxValueFound = 1.0;
                 minMaxPosition = ${r?a?m:A:`wR * ${h} + wC`};
@@ -1424,7 +1424,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         float avgValue = 0.0;
         count = 0.0;
 
-        for (int wR = 0; wR < ${c};
+        for (int wR = 0; wR < ${u};
             wR += ${l}) {
           int xR = xRCorner + wR;
 
@@ -1433,13 +1433,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
 
           for (int wC = 0; wC < ${b}; wC += 4) {
-            int xC = xCCorner + wC * ${u};
+            int xC = xCCorner + wC * ${c};
 
             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)
+              getValue(batch, xR, xC + ${c}, d),
+              getValue(batch, xR, xC + 2 * ${c}, d),
+              getValue(batch, xR, xC + 3 * ${c}, d)
             );
 
             ${x}
@@ -1458,7 +1458,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           } else if (${_===2}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
-              getValue(batch, xR, xC + ${u}, d),
+              getValue(batch, xR, xC + ${c}, d),
               initializationValue,
               initializationValue
             );
@@ -1467,8 +1467,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           } else if (${_===3}) {
             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 + ${c}, d),
+              getValue(batch, xR, xC + 2 * ${c}, d),
               initializationValue
             );
 
@@ -1477,7 +1477,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(${w});
       }
-    `}},aA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,c=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let T=">=";this.userCode=`
+    `}},aA=class{constructor(e,t,n,r=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,c=e.dilationDepth,u=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let C=">=";this.userCode=`
         const ivec3 strides =
             ivec3(${i}, ${o}, ${l});
         const ivec3 pads = ivec3(${m}, ${A}, ${y});
@@ -1499,7 +1499,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           int minMaxPosition = 0;
 
           for (int wD = 0; wD < ${d};
-              wD += ${u}) {
+              wD += ${c}) {
             int xD = xDCorner + wD;
 
             if (xD < 0 || xD >= ${e.inDepth}) {
@@ -1507,7 +1507,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             }
 
             for (int wR = 0; wR < ${p};
-                wR += ${c}) {
+                wR += ${u}) {
               int xR = xRCorner + wR;
 
               if (xR < 0 || xR >= ${e.inHeight}) {
@@ -1528,7 +1528,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 // use the current value.
                 float currMinMaxValue = mix(
                     value, minMaxValue, minMaxValueFound);
-                if (value ${T} currMinMaxValue) {
+                if (value ${C} currMinMaxValue) {
                   minMaxValue = value;
                   minMaxValueFound = 1.0;
                   minMaxPosition = ${r?a?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${p} * ${f} +
@@ -1539,7 +1539,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let b="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,I=s%4,S=`
+      `;return}let b="max",_=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(_="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,T=`
       if (${g}) {
         avgValue += dot(values, ones);
       } else {
@@ -1579,7 +1579,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         count = 0.0;
 
         for (int wD = 0; wD < ${d};
-            wD += ${u}) {
+            wD += ${c}) {
           int xD = xDCorner + wD;
 
           if (xD < 0 || xD >= ${e.inDepth}) {
@@ -1587,7 +1587,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
 
           for (int wR = 0; wR < ${p};
-            wR += ${c}) {
+            wR += ${u}) {
             int xR = xRCorner + wR;
 
             if (xR < 0 || xR >= ${e.inHeight}) {
@@ -1604,11 +1604,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 getValue(batch, xD, xR, xC + 3 * ${h}, ch)
               );
 
-              ${S}
+              ${T}
             }
 
             int xC = xCCorner + ${x};
-            if (${I===1}) {
+            if (${N===1}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
                 initializationValue,
@@ -1616,8 +1616,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 initializationValue
               );
 
-              ${S}
-            } else if (${I===2}) {
+              ${T}
+            } else if (${N===2}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
                 getValue(batch, xD, xR, xC + ${h}, ch),
@@ -1625,8 +1625,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 initializationValue
               );
 
-              ${S}
-            } else if (${I===3}) {
+              ${T}
+            } else if (${N===3}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
                 getValue(batch, xD, xR, xC + ${h}, ch),
@@ -1634,14 +1634,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 initializationValue
               );
 
-              ${S}
+              ${T}
             }
           }
           setOutput(${_});
         }
       }
-    `}};function SW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return zn({inputs:{x:a},backend:n});let h=new dc(c,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var TW={kernelName:cs,backendName:"webgl",kernelFunc:SW};function CW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,l,u),d=new aA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var EW={kernelName:cu,backendName:"webgl",kernelFunc:CW},RW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,c=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
-      const ivec2 pads = ivec2(${u}, ${c});
+    `}};function xW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return zn({inputs:{x:a},backend:n});let h=new pc(u,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var wW={kernelName:cs,backendName:"webgl",kernelFunc:xW};function bW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,l,c),d=new aA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var _W={kernelName:hu,backendName:"webgl",kernelFunc:bW},vW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,c=o-1-e.padInfo.top,u=l-1-e.padInfo.left,h=1/(t*n);this.userCode=`
+      const ivec2 pads = ivec2(${c}, ${u});
       const float avgMultiplier = float(${h});
 
       void main() {
@@ -1682,7 +1682,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},FW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=c-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
+    `}},kW=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=u-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=`
       const ivec3 pads = ivec3(${p}, ${f}, ${m});
       const float avgMultiplier = float(${A});
 
@@ -1701,7 +1701,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         // ? = to be determined. : = across all values in that axis.
         float dotProd = 0.0;
 
-        for (int wD = 0; wD < ${c};
+        for (int wD = 0; wD < ${u};
             wD += ${o}) {
           float dyD = float(dyDCorner + wD) / ${a}.0;
 
@@ -1721,7 +1721,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             int idyR = int(dyR);
 
             for (int wC = 0; wC < ${d};
-                wC += ${u}) {
+                wC += ${c}) {
               float dyC = float(dyCCorner + wC) / ${i}.0;
 
               if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
@@ -1738,7 +1738,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function MW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new FW(d);return n.runWebGLProgram(p,[a],i.dtype)}var $W={kernelName:Sh,backendName:"webgl",kernelFunc:MW};function DW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;kl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=r,c=R.computePool2DInfo(i.shape,o,l,1,u),h=new RW(c);return n.runWebGLProgram(h,[a],i.dtype)}var OW={kernelName:Ih,backendName:"webgl",kernelFunc:DW};function zW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return mp({a,b:s,transposeA:i,transposeB:o,backend:n})}var PW={kernelName:hs,backendName:"webgl",kernelFunc:zW},LW=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};function IW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new kW(d);return n.runWebGLProgram(p,[a],i.dtype)}var NW={kernelName:Th,backendName:"webgl",kernelFunc:IW};function SW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;kl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:c}=r,u=R.computePool2DInfo(i.shape,o,l,1,c),h=new vW(u);return n.runWebGLProgram(h,[a],i.dtype)}var TW={kernelName:Sh,backendName:"webgl",kernelFunc:SW};function CW(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return Ap({a,b:s,transposeA:i,transposeB:o,backend:n})}var EW={kernelName:hs,backendName:"webgl",kernelFunc:CW},RW=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         float x = getXAtOutCoords();
         float mean = getMeanAtOutCoords();
@@ -1748,7 +1748,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         float inv = scale * inversesqrt(variance + float(${s}));
         setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
       }
-    `}},WW=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}},MW=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],R.assertAndGetBroadcastShape(e,t),R.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(R.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(R.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         vec4 offset = ${i};
         vec4 scale = ${o};
@@ -1761,7 +1761,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         setOutput((x - mean) * inv + offset);
       }
-    `}},BW=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[r,a,s],c=null;i!=null&&(c=i.shape,u.push(i));let h=null;o!=null&&(h=o.shape,u.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new WW(r.shape,a.shape,s.shape,c,h,l):new LW(r.shape,a.shape,s.shape,c,h,l);return t.runWebGLProgram(d,u,u[0].dtype)},VW={kernelName:vs,backendName:"webgl",kernelFunc:BW},jW=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ct(this.rank),n=`uniform int start[${this.rank}];`,r=UW(this.rank),a,s=e.map((i,o)=>`sourceLoc.${sA[o]} = start[${o}] + coords.${sA[o]};`);a=`
+    `}},FW=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let c=[r,a,s],u=null;i!=null&&(u=i.shape,c.push(i));let h=null;o!=null&&(h=o.shape,c.push(o));let d=J().getBool("WEBGL_PACK_NORMALIZATION")?new MW(r.shape,a.shape,s.shape,u,h,l):new RW(r.shape,a.shape,s.shape,u,h,l);return t.runWebGLProgram(d,c,c[0].dtype)},$W={kernelName:vs,backendName:"webgl",kernelFunc:FW},OW=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ut(this.rank),n=`uniform int start[${this.rank}];`,r=DW(this.rank),a,s=e.map((i,o)=>`sourceLoc.${sA[o]} = start[${o}] + coords.${sA[o]};`);a=`
         ${t} sourceLoc;
         ${t} coords = getOutputCoords();
         ${s.join(`
@@ -1772,7 +1772,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${a}
         setOutput(getSource(${r}));
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},sA=["x","y","z","w","u","v"];function UW(e){if(e===1)return"sourceLoc";if(e<=6)return sA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var HW=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ct(this.rank),n=mn("coords",this.rank),r=mn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${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)}}},sA=["x","y","z","w","u","v"];function DW(e){if(e===1)return"sourceLoc";if(e<=6)return sA.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var zW=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=ut(this.rank),n=mn("coords",this.rank),r=mn("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${r.slice(-2).join()})`,s=`getChannel(getSource(${r.join()}), ${a})`,i=`
       result.x = ${s};
       if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
         ++${r[this.rank-1]};
@@ -1790,7 +1790,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
       }
     `,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(`
+            ${t}(${e.map((c,u)=>`start[${u}]`).join()});`:e.map((c,u)=>`${r[u]} = ${n[u]} + start[${u}];`).join(`
 `);this.userCode=`
       uniform int start[${this.rank}];
       void main() {
@@ -1802,7 +1802,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${o}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function GW(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=cn.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function pc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=cn.parseSliceParams(a,s,i);if(cn.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=WP(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:u}=n.texData.get(a.dataId),c=cn.isSliceContinous(a.shape,o,l);if(u||!c){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new HW(l):new jW(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),GW(a,o,l,n)}var qW={kernelName:Wo,backendName:"webgl",kernelFunc:pc},XW=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=R.getReshaped(a.shape,s,o),u=R.getPermuted(l.length,s.length),c=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(c,i,s.length),p=[],f=ye({inputs:{x:a},backend:n,attrs:{shape:l}}),m=In({inputs:{x:f},backend:n,attrs:{perm:u}}),A=ye({inputs:{x:m},backend:n,attrs:{shape:c}}),y=pc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},KW={kernelName:hu,backendName:"webgl",kernelFunc:XW};function ZW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),u=F_(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var YW={kernelName:Th,backendName:"webgl",kernelFunc:ZW},JW="return float(a != b);",ib=nn({opSnippet:JW,dtype:"bool"}),QW={kernelName:To,backendName:"webgl",kernelFunc:ib};function fc(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return zn({inputs:{x:a.complexTensorInfos.real},backend:n})}var eB={kernelName:Kh,backendName:"webgl",kernelFunc:fc},tB="return float(int(x));";function nB(e,t){let n=new Va(e.shape,tB),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function iA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return zn({inputs:{x:a},backend:n});let i=Ft(a.shape),o=iA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Ua({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=fc({inputs:{input:a},backend:n}),o=iA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=zn({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return nB(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=ib({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var rB={kernelName:ds,backendName:"webgl",kernelFunc:iA},ob="return ceil(x);",aB=Ze({opSnippet:ob,packedOpSnippet:ob,cpuKernelImpl:bP}),sB={kernelName:ps,backendName:"webgl",kernelFunc:aB},iB=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${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 PW(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=cn.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function fc(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=cn.parseSliceParams(a,s,i);if(cn.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=MP(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:c}=n.texData.get(a.dataId),u=cn.isSliceContinous(a.shape,o,l);if(c||!u){let h=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new zW(l):new OW(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),PW(a,o,l,n)}var LW={kernelName:Wo,backendName:"webgl",kernelFunc:fc},WW=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=R.getReshaped(a.shape,s,o),c=R.getPermuted(l.length,s.length),u=R.getReshapedPermuted(a.shape,s,o),h=R.getSliceBeginCoords(i,s.length),d=R.getSliceSize(u,i,s.length),p=[],f=ye({inputs:{x:a},backend:n,attrs:{shape:l}}),m=Nn({inputs:{x:f},backend:n,attrs:{perm:c}}),A=ye({inputs:{x:m},backend:n,attrs:{shape:u}}),y=fc({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},BW={kernelName:du,backendName:"webgl",kernelFunc:WW};function VW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),c=Fb(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}var UW={kernelName:Ch,backendName:"webgl",kernelFunc:VW},jW="return float(a != b);",o_=nn({opSnippet:jW,dtype:"bool"}),HW={kernelName:To,backendName:"webgl",kernelFunc:o_};function mc(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return zn({inputs:{x:a.complexTensorInfos.real},backend:n})}var GW={kernelName:Zh,backendName:"webgl",kernelFunc:mc},qW="return float(int(x));";function XW(e,t){let n=new Va(e.shape,qW),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function iA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return zn({inputs:{x:a},backend:n});let i=Mt(a.shape),o=iA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Ua({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=mc({inputs:{input:a},backend:n}),o=iA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=zn({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return XW(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=o_({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var KW={kernelName:ds,backendName:"webgl",kernelFunc:iA},l_="return ceil(x);",ZW=Ze({opSnippet:l_,packedOpSnippet:l_,cpuKernelImpl:fP}),YW={kernelName:ps,backendName:"webgl",kernelFunc:ZW},JW=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1815,7 +1815,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         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)}}},oB=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
+    `}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)}}},QW=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1829,7 +1829,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         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 lB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new oB(a.shape):o=new iB(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var uB={kernelName:Sa,backendName:"webgl",kernelFunc:lB},cB=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
+    `}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 eB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=r,o;J().getBool("WEBGL_PACK_CLIP")?o=new QW(a.shape):o=new JW(a.shape);let l=o.getCustomSetupFunc(s,i);return n.runWebGLProgram(o,[a],a.dtype,l)}var tB={kernelName:Sa,backendName:"webgl",kernelFunc:eB},nB=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
       void main() {
         float re = abs(getRealAtOutCoords());
         float im = abs(getImagAtOutCoords());
@@ -1842,7 +1842,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
         );
       }
-    `}};function lb(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function hB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new cB(r.shape),i=[lb(r,a.complexTensorInfos.real),lb(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var dB={kernelName:du,backendName:"webgl",kernelFunc:hB},pB=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
+    `}};function u_(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function rB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=n.texData.get(r.dataId),s=new nB(r.shape),i=[u_(r,a.complexTensorInfos.real),u_(r,a.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var aB={kernelName:pu,backendName:"webgl",kernelFunc:rB},sB=class{constructor(e){this.outputShape=[],this.outputShape=R.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let r=t.length,a=t[t.length-1];n.push(`else setOutput(getT${r}(yR, yC-${a}));`),this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int yR = coords.x;
@@ -1851,18 +1851,18 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${n.join(`
         `)}
       }
-    `}},fB=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ct(r),s=mn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],u=i.slice(-2),c=i.join(),h=`if (${l} < ${o[0]}) {
+    `}},iB=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=R.computeOutShape(e,t);let n=this.outputShape,r=n.length,a=ut(r),s=mn("coords",r),i=["x","y","z","w","u","v"].slice(0,r);this.variableNames=e.map((f,m)=>`T${m}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let f=1;f<o.length;f++)o[f]=o[f-1]+e[f][t];let l=i[t],c=i.slice(-2),u=i.join(),h=`if (${l} < ${o[0]}) {
         return getChannel(
-            getT0(${c}), vec2(${u.join()}));
+            getT0(${u}), vec2(${c.join()}));
         }`;for(let f=1;f<o.length;f++){let m=o[f-1];h+=`
         if (${l} < ${o[f]}  && ${l} >= ${o[f-1]}) {
           return getChannel(
-            getT${f}(${yp(i,l,m)}),
-            vec2(${yp(u,l,m)}));
+            getT${f}(${gp(i,l,m)}),
+            vec2(${gp(c,l,m)}));
         }`}let d=o.length,p=o[o.length-1];h+=`
         return getChannel(
-          getT${d}(${yp(i,l,p)}),
-          vec2(${yp(u,l,p)}));`,this.userCode=`
+          getT${d}(${gp(i,l,p)}),
+          vec2(${gp(c,l,p)}));`,this.userCode=`
       float getValue(${i.map(f=>"int "+f)}) {
         ${h}
       }
@@ -1888,7 +1888,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(result);
       }
-    `}};function yp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function gp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return zn({inputs:{x:a.complexTensorInfos.imag},backend:n})}var mB={kernelName:Vh,backendName:"webgl",kernelFunc:gp};function Ml(e,t,n){let r=e[0].dtype;if(r==="complex64"){let u=e.map(f=>fc({inputs:{input:f},backend:n})),c=e.map(f=>gp({inputs:{input:f},backend:n})),h=Ml(u,t,n),d=Ml(c,t,n),p=Ua({inputs:{real:h,imag:d},backend:n});return u.forEach(f=>n.disposeIntermediateTensorInfo(f)),c.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:u,outShape:c}=ub(e,t,n),h=u.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=u[0].shape[0]===1,p=vP(h,c,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return u.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(e.length/2),c=Ml(e.slice(0,u),t,n),h=Ml(e.slice(u),t,n),d=Ml([c,h],t,n);return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let u=new fB(e.map(c=>c.shape),t);return n.runWebGLProgram(u,e,r)}let{tensors2D:a,outShape:s}=ub(e,t,n),i=new pB(a.map(u=>u.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(u=>n.disposeIntermediateTensorInfo(u));let l=ye({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function ub(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ye({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function cb(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(u=>v.sizeFromShape(u.shape)>0);if(o.length===1)return zn({inputs:{x:o[0]},backend:n});let l=o.map(u=>u.shape);return R.assertParamsConsistent(l,s),Ml(o,s,n)}var AB={kernelName:so,backendName:"webgl",kernelFunc:cb},hb=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,w="",b="";n&&(r?w=`float activation(float a) {
+    `}};function gp(e,t,n){let r=e.indexOf(t);return e.map((a,s)=>s===r?`${a} - ${n}`:a).join()}function xp(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return zn({inputs:{x:a.complexTensorInfos.imag},backend:n})}var oB={kernelName:Uh,backendName:"webgl",kernelFunc:xp};function Fl(e,t,n){let r=e[0].dtype;if(r==="complex64"){let c=e.map(f=>mc({inputs:{input:f},backend:n})),u=e.map(f=>xp({inputs:{input:f},backend:n})),h=Fl(c,t,n),d=Fl(u,t,n),p=Ua({inputs:{real:h,imag:d},backend:n});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),u.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),p}if(r==="string"){let{tensors2D:c,outShape:u}=c_(e,t,n),h=c.map(A=>({vals:n.readSync(A.dataId),shape:A.shape})),d=c[0].shape[0]===1,p=mP(h,u,r,d),f=R.computeOutShape(e.map(A=>A.shape),t),m=n.makeTensorInfo(f,r,p);return c.forEach(A=>n.disposeIntermediateTensorInfo(A)),m}if(e.length>J().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),u=Fl(e.slice(0,c),t,n),h=Fl(e.slice(c),t,n),d=Fl([u,h],t,n);return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),d}if(J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new iB(e.map(u=>u.shape),t);return n.runWebGLProgram(c,e,r)}let{tensors2D:a,outShape:s}=c_(e,t,n),i=new sB(a.map(c=>c.shape)),o=n.runWebGLProgram(i,a,r);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let l=ye({inputs:{x:o},attrs:{shape:s},backend:n});return n.disposeIntermediateTensorInfo(o),l}function c_(e,t,n){let r=R.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ye({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:r}}function h_(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r,s=v.parseAxisParam(a,t[0].shape)[0],i=R.computeOutShape(t.map(c=>c.shape),s);if(v.sizeFromShape(i)===0)return n.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(c=>v.sizeFromShape(c.shape)>0);if(o.length===1)return zn({inputs:{x:o[0]},backend:n});let l=o.map(c=>c.shape);return R.assertParamsConsistent(l,s),Fl(o,s,n)}var lB={kernelName:so,backendName:"webgl",kernelFunc:h_},d_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,c=e.dilationHeight,u=e.dilationWidth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",A=m?1:2,y=m?2:3,g=m?3:1,w="",b="";n&&(r?w=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?w=`float activation(float a) {
@@ -1918,14 +1918,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         // ? = to be determined. : = across all values in that axis.
         float dotProd = 0.0;
         for (int wR = 0; wR < ${h}; wR++) {
-          int xR = xRCorner + wR * ${u};
+          int xR = xRCorner + wR * ${c};
 
           if (xR < 0 || xR >= ${e.inHeight}) {
             continue;
           }
 
           for (int wC = 0; wC < ${d}; wC++) {
-            int xC = xCCorner + wC * ${c};
+            int xC = xCCorner + wC * ${u};
 
             if (xC < 0 || xC >= ${e.inWidth}) {
               continue;
@@ -2022,7 +2022,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${b}
         setOutput(result);
       }
-    `}},yB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
+    `}},uB=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,c=e.dilationWidth,u=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=`
       const ivec3 strides = ivec3(${a}, ${s}, ${i});
       const ivec3 pads = ivec3(${t}, ${n}, ${r});
 
@@ -2040,7 +2040,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         // 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++) {
+        for (int wF = 0; wF < ${u}; wF++) {
           int xF = xFCorner + wF * ${o};
 
           if (xF < 0 || xF >= ${e.inDepth}) {
@@ -2055,7 +2055,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             }
 
             for (int wC = 0; wC < ${d}; wC++) {
-              int xC = xCCorner + wC * ${u};
+              int xC = xCCorner + wC * ${c};
 
               if (xC < 0 || xC >= ${e.inWidth}) {
                 continue;
@@ -2110,18 +2110,18 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},gB=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:u,dilationHeight:c,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=fn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let b=0;b<=1;b++)for(let _=0;_<=1;_++)w+=`
+    `}},cB=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:c,dilationHeight:u,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=fn(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let b=0;b<=1;b++)for(let _=0;_<=1;_++)w+=`
           blockIndex = rc.y + ${_};
           pos = rc.x + ${b};
 
           if(blockIndex < ${e[1]} && pos < ${e[0]}) {
             offsetY = int(blockIndex / (${l})) * ${i} - ${p};
-            d0 = offsetY + ${c} * (pos / ${f});
+            d0 = offsetY + ${u} * (pos / ${f});
 
             if(d0 < ${t[y]} && d0 >= 0) {
 
               offsetX = int(mod(float(blockIndex), ${l}.) * ${s}. - ${d}.);
-              d1 = offsetX + ${u} * (int(mod(float(pos), ${f}.) / ${a}.));
+              d1 = offsetX + ${c} * (int(mod(float(pos), ${f}.) / ${a}.));
 
               if(d1 < ${t[g]} && d1 >= 0) {
 
@@ -2154,7 +2154,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         ${m.output} = result;
       }
-    `}};function db({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=r.texData.get(e.dataId),c=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&c>eb,w=l[2]%2!=0&&!!u.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=ye({inputs:{x:e},backend:r,attrs:{shape:[1,b,n.inChannels]}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),I=mp({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=ye({inputs:{x:I},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(I)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},x=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(ic(u.shape,_.shape),()=>`packed reshape ${u.shape} to ${_.shape} isn't free`);let I=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(I);let S=mp({a:_,b:I,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),T=r.texData.get(S.dataId);v.assert(T.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=x,T.shape=n.outShape,A=zn({inputs:{x:S},backend:r}),A.shape=n.outShape,y.push(S)}for(let b of y)r.disposeIntermediateTensorInfo(b);return A}function pb({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*u*c,A=d*h,y=[m,A],g=!0,w=!1,b=[],_=ye({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(_),b.push(x);let I=new gB(y,_.shape,n),S=r.runWebGLProgram(I,[_],"float32"),T=ye({inputs:{x:S},backend:r,attrs:{shape:[1,y[0],y[1]]}});b.push(S),b.push(T);let M=a!=null,D=s!=null,z=o==="leakyrelu",B=o?pp(o,!0):null,U=new X_(T.shape,x.shape,[1,A,n.outChannels],g,w,M,B,D,z),j=[T,x];if(a&&j.push(a),D&&j.push(s),z){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));j.push(Y),b.push(Y)}let X=r.runWebGLProgram(U,j,"float32"),H=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=ye({inputs:{x:X},backend:r,attrs:{shape:H}});b.push(X);for(let Y of b)r.disposeIntermediateTensorInfo(Y);return ee}function xB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!1,h),p;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))p=db({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=pb({x:a,filter:s,convInfo:d,backend:n});else{let m=new hb(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=ye({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var wB={kernelName:fs,backendName:"webgl",kernelFunc:xB},_B=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
+    `}};function p_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,c=r.texData.get(e.dataId),u=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&u>t_,w=l[2]%2!=0&&!!c.isPacked;if(g||!J().getBool("WEBGL_LAZILY_UNPACK")||!J().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=ye({inputs:{x:e},backend:r,attrs:{shape:[1,b,n.inChannels]}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=Ap({a:_,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=ye({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(_),y.push(x),y.push(N)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},x=c.shape;c.shape=c.shape.slice(),c.shape[c.shape.length-2]++,v.assert(oc(c.shape,_.shape),()=>`packed reshape ${c.shape} to ${_.shape} isn't free`);let N=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let T=Ap({a:_,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),C=r.texData.get(T.dataId);v.assert(C.isPacked,()=>"batchMatMul result is expected to be packed"),c.shape=x,C.shape=n.outShape,A=zn({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let b of y)r.disposeIntermediateTensorInfo(b);return A}function f_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:c,inChannels:u,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*c*u,A=d*h,y=[m,A],g=!0,w=!1,b=[],_=ye({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(_),b.push(x);let N=new cB(y,_.shape,n),T=r.runWebGLProgram(N,[_],"float32"),C=ye({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});b.push(T),b.push(C);let F=a!=null,z=s!=null,B=o==="leakyrelu",V=o?fp(o,!0):null,U=new Kb(C.shape,x.shape,[1,A,n.outChannels],g,w,F,V,z,B),j=[C,x];if(a&&j.push(a),z&&j.push(s),B){let Y=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));j.push(Y),b.push(Y)}let X=r.runWebGLProgram(U,j,"float32"),G=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=ye({inputs:{x:X},backend:r,attrs:{shape:G}});b.push(X);for(let Y of b)r.disposeIntermediateTensorInfo(Y);return ee}function hB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!1,h),p;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))p=p_({x:a,filter:s,convInfo:d,backend:n});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=f_({x:a,filter:s,convInfo:d,backend:n});else{let m=new d_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=ye({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var dB={kernelName:fs,backendName:"webgl",kernelFunc:hB},pB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2196,15 +2196,15 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},bB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,u=s?2:3,c=s?3:1;this.userCode=`
+    `}},fB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,c=s?2:3,u=s?3:1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
         ivec4 coords = getOutputCoords();
         int batch = coords[0];
-        int d1 = coords[${c}];
+        int d1 = coords[${u}];
 
-        ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - pads;
+        ivec2 dyCorner = ivec2(coords[${l}], coords[${c}]) - pads;
         int dyRCorner = dyCorner.x;
         int dyCCorner = dyCorner.y;
 
@@ -2249,7 +2249,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},vB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
+    `}},mB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
       void main() {
         ivec5 coords = getOutputCoords();
         int wF = coords.x;
@@ -2291,8 +2291,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},kB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=r-1-e.padInfo.left;this.userCode=`
-      const ivec3 pads = ivec3(${o}, ${l}, ${u});
+    `}},AB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,c=r-1-e.padInfo.left;this.userCode=`
+      const ivec3 pads = ivec3(${o}, ${l}, ${c});
 
       void main() {
         ivec5 coords = getOutputCoords();
@@ -2348,12 +2348,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function NB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:c}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,c,i,1,o,u,!1,h),p=new _B(d);return n.runWebGLProgram(p,[a,s],"float32")}var IB={kernelName:Eh,backendName:"webgl",kernelFunc:NB};function SB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:c}=r,h=R.convertConv2DDataFormat(u),d=R.computeConv2DInfo(i,s.shape,o,1,l,c,!1,h),p=new bB(d);return n.runWebGLProgram(p,[a,s],"float32")}var TB={kernelName:ms,backendName:"webgl",kernelFunc:SB};function CB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeConv3DInfo(a.shape,s.shape,i,l,o),c=new yB(u);return n.runWebGLProgram(c,[a,s],"float32")}var EB={kernelName:pu,backendName:"webgl",kernelFunc:CB};function RB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,u=R.computeConv3DInfo(a.shape,l,i,1,o),c=new vB(u);return n.runWebGLProgram(c,[a,s],"float32")}var FB={kernelName:Rh,backendName:"webgl",kernelFunc:RB};function MB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,u=R.computeConv3DInfo(l,s.shape,o,1,i),c=new kB(u);return n.runWebGLProgram(c,[a,s],"float32")}var $B={kernelName:Fh,backendName:"webgl",kernelFunc:MB},DB=q_+`
+    `}};function yB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:c,filterShape:u}=r,h=R.convertConv2DDataFormat(l),d=R.computeConv2DInfo(a.shape,u,i,1,o,c,!1,h),p=new pB(d);return n.runWebGLProgram(p,[a,s],"float32")}var gB={kernelName:Rh,backendName:"webgl",kernelFunc:yB};function xB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:c,dimRoundingMode:u}=r,h=R.convertConv2DDataFormat(c),d=R.computeConv2DInfo(i,s.shape,o,1,l,u,!1,h),p=new fB(d);return n.runWebGLProgram(p,[a,s],"float32")}var wB={kernelName:ms,backendName:"webgl",kernelFunc:xB};function bB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeConv3DInfo(a.shape,s.shape,i,l,o),u=new uB(c);return n.runWebGLProgram(u,[a,s],"float32")}var _B={kernelName:fu,backendName:"webgl",kernelFunc:bB};function vB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,c=R.computeConv3DInfo(a.shape,l,i,1,o),u=new mB(c);return n.runWebGLProgram(u,[a,s],"float32")}var kB={kernelName:Mh,backendName:"webgl",kernelFunc:vB};function IB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,c=R.computeConv3DInfo(l,s.shape,o,1,i),u=new AB(c);return n.runWebGLProgram(u,[a,s],"float32")}var NB={kernelName:Fh,backendName:"webgl",kernelFunc:IB},SB=Xb+`
   return cos(x);
-`,OB=Ze({opSnippet:DB}),zB={kernelName:As,backendName:"webgl",kernelFunc:OB},PB=`
+`,TB=Ze({opSnippet:SB}),CB={kernelName:As,backendName:"webgl",kernelFunc:TB},EB=`
   float e2x = exp(-x);
   return (e2x + 1.0 / e2x) / 2.0;
-`,LB=Ze({opSnippet:PB}),WB={kernelName:io,backendName:"webgl",kernelFunc:LB},BB=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[c,h]=n;this.outputShape=[u,c,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=c>1?[`${(i-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,b]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
+`,RB=Ze({opSnippet:EB}),MB={kernelName:io,backendName:"webgl",kernelFunc:RB},FB=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[c]=t,[u,h]=n;this.outputShape=[c,u,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=u>1?[`${(i-1)/(u-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,b]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
       const float height_ratio = float(${m});
       const float width_ratio = float(${g});
       void main() {
@@ -2414,21 +2414,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           setOutput(newValue);
         }
       }
-    `}},VB=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=r,c=new BB(a.shape,s.shape,o,l,u);return n.runWebGLProgram(c,[a,s,i],"float32")},UB={kernelName:oo,backendName:"webgl",kernelFunc:VB},Ab=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${fb(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
+    `}},$B=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:c}=r,u=new FB(a.shape,s.shape,o,l,c);return n.runWebGLProgram(u,[a,s,i],"float32")},DB={kernelName:oo,backendName:"webgl",kernelFunc:$B},y_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${m_(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=`
       uniform float index;
       void main() {
-        ${ct(r)} coords = getOutputCoords();
-        int end = ${mb(r,"coords")};
+        ${ut(r)} coords = getOutputCoords();
+        int end = ${A_(r,"coords")};
         float val = ${a};
         int pow2 = int(pow(2.0, index));
         if (${i}) {
           int idx = ${o};
-          ${mb(r,"coords")} = idx;
-          val += getX(${fb(r,"coords")});
+          ${A_(r,"coords")} = idx;
+          val += getX(${m_(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 fb(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 ${e} is not yet supported`)}function mb(e,t){if(e===1)return`${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 ${e} is not yet supported`)}function jB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,u=R.getAxesPermutation([s],l),c=a;u!=null&&(c=In({inputs:{x:a},backend:n,attrs:{perm:u}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=c.shape[h],p=zn({inputs:{x:c},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new Ab(c.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new Ab(c.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(u!=null){let f=R.getUndoAxesPermutation(u),m=In({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(c),m}return p}var HB={kernelName:ys,backendName:"webgl",kernelFunc:jB};function GB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),u=n.readSync(s.dataId),c=F_(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=_P(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var qB={kernelName:Mh,backendName:"webgl",kernelFunc:GB},XB=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function m_(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 ${e} is not yet supported`)}function A_(e,t){if(e===1)return`${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 ${e} is not yet supported`)}function OB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,c=R.getAxesPermutation([s],l),u=a;c!=null&&(u=Nn({inputs:{x:a},backend:n,attrs:{perm:c}}));let h=R.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=u.shape[h],p=zn({inputs:{x:u},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new y_(u.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new y_(u.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(c!=null){let f=R.getUndoAxesPermutation(c),m=Nn({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),m}return p}var zB={kernelName:ys,backendName:"webgl",kernelFunc:OB};function PB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),c=n.readSync(s.dataId),u=Fb(l,c,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}else if(a.shape.length===2){let l=n.bufferSync(a),c=n.bufferSync(s),u=pP(l,c,i,o);return n.makeTensorInfo(u.shape,s.dtype,u.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var LB={kernelName:$h,backendName:"webgl",kernelFunc:PB},WB=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];
@@ -2447,7 +2447,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
       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 KB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],c=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=u*s,p=c/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new XB(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var ZB={kernelName:lo,backendName:"webgl",kernelFunc:KB},yb=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
+  `}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 BB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],c=i==="NHWC"?a.shape[2]:a.shape[3],u=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=c*s,p=u/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new WB(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var VB={kernelName:lo,backendName:"webgl",kernelFunc:BB},g_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:a?A=`float activation(float a) {
@@ -2460,7 +2460,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         `,y="result = activation(result);");let g=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${A}
 
-      const ivec2 strides = ivec2(${u}, ${c});
+      const ivec2 strides = ivec2(${c}, ${u});
       const ivec2 pads = ivec2(${o}, ${l});
 
       void main() {
@@ -2503,13 +2503,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${y}
         setOutput(result);
       }
-    `}},gb=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`
+    `}},x_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,c=e.strideHeight,u=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let b=0;b<p;b++)for(let _=0;_<f;_++)A+=`
           vec4 xTexelR${b}C${_*2} = vec4(0.);
           vec4 wR${b}C${_} = vec4(0.);
           vec4 xR${b}C${_} = vec4(0.);`;for(let b=0;b<p;b++)for(let _=0;_<m;_++){let x=_*2;if(A+=`
           xR = xRCorner + ${b*h};
           xC = xCCorner + ${x*d};
-        `,c===1){if(x<f&&(l%2==1?A+=`
+        `,u===1){if(x<f&&(l%2==1?A+=`
                 xCOffset = xC + 1;
                 if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) {
                   xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
@@ -2545,8 +2545,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 }
 
                 xR${b}C${x} = xTexelR${b}C${x};
-              `,x+1<f)){let I=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
-                  xCOffset = xC + ${l%2} + ${I};
+              `,x+1<f)){let N=l%2==0?v.nearestLargerEven(d):d;d%2==0&&l%2==1||d%2!=0&&l%2!=1?(A+=`
+                  xCOffset = xC + ${l%2} + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
@@ -2564,7 +2564,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                   xR${b}C${x+1} = vec4(
                     xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.xy);
                 `):A+=`
-                  xCOffset = xC + ${I};
+                  xCOffset = xC + ${N};
 
                   if(xR >= 0 && xR < ${s} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
@@ -2575,7 +2575,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                 `}}else x<f&&(A+=`
               if(xR >= 0 && xR < ${s}) {
             `,l%2==1?(A+=`
-                xCOffset = xC + 1 - ${c};
+                xCOffset = xC + 1 - ${u};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
                   xTexelR${b}C${x} = getX(batch, xR, xCOffset, d1);
                 } else {
@@ -2592,7 +2592,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                   xTexelR${b}C${x}.zw, xTexelR${b}C${x+2}.zw);
               `,x+1<f&&(A+=`
                   vec4 final = vec4(0.);
-                  xCOffset = xC + 1 + ${c};
+                  xCOffset = xC + 1 + ${u};
                   if(xCOffset >= 0 && xCOffset < ${i}) {
                     final = getX(batch, xR, xCOffset, d1);
                   }
@@ -2604,7 +2604,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
                   xTexelR${b}C${x} = vec4(0.);
                 }
 
-                xCOffset = xC + ${c};
+                xCOffset = xC + ${u};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
                   xTexelR${b}C${x+2} = getX(batch, xR, xCOffset, d1);
                 } else {
@@ -2633,7 +2633,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }`,g="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${y}
 
-      const ivec2 strides = ivec2(${u}, ${c});
+      const ivec2 strides = ivec2(${c}, ${u});
       const ivec2 pads = ivec2(${o}, ${l});
 
       void main() {
@@ -2656,7 +2656,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${g}
         setOutput(result);
       }
-    `}};function YB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=r,c=l;c==null&&(c=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new gb(h):d=new yb(h),n.runWebGLProgram(d,[a,s],"float32")}var JB={kernelName:gs,backendName:"webgl",kernelFunc:YB},QB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
+    `}};function UB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:c}=r,u=l;u==null&&(u=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let h=R.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!0),d;return J().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new x_(h):d=new g_(h),n.runWebGLProgram(d,[a,s],"float32")}var jB={kernelName:gs,backendName:"webgl",kernelFunc:UB},HB=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2691,7 +2691,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},eV=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
+    `}},GB=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
       const ivec2 pads = ivec2(${s}, ${i});
 
       void main() {
@@ -2736,15 +2736,15 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function tV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:c}=r,h=R.computeConv2DInfo(a.shape,c,i,o,l,u,!0),d=new QB(h);return n.runWebGLProgram(d,[a,s],"float32")}var nV={kernelName:$h,backendName:"webgl",kernelFunc:tV};function rV(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:c}=r,h=R.computeConv2DInfo(c,s.shape,i,o,l,u,!0),d=new eV(h);return n.runWebGLProgram(d,[a,s],"float32")}var aV={kernelName:Dh,backendName:"webgl",kernelFunc:rV},sV=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
+    `}};function qB(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,filterShape:u}=r,h=R.computeConv2DInfo(a.shape,u,i,o,l,c,!0),d=new HB(h);return n.runWebGLProgram(d,[a,s],"float32")}var XB={kernelName:Dh,backendName:"webgl",kernelFunc:qB};function KB(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:c,inputShape:u}=r,h=R.computeConv2DInfo(u,s.shape,i,o,l,c,!0),d=new GB(h);return n.runWebGLProgram(d,[a,s],"float32")}var ZB={kernelName:Oh,backendName:"webgl",kernelFunc:KB},YB=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 iV(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=ye({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new sV(s),l=n.runWebGLProgram(o,[i],i.dtype),u=ye({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var oV={kernelName:Oh,backendName:"webgl",kernelFunc:iV},lV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:c,left:h}=r;this.userCode=`
+    `}};function JB(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=ye({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new YB(s),l=n.runWebGLProgram(o,[i],i.dtype),c=ye({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),c}var QB={kernelName:zh,backendName:"webgl",kernelFunc:JB},eV=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:c}=e,{top:u,left:h}=r;this.userCode=`
       const ivec2 strides = ivec2(${a}, ${s});
-      const ivec2 pads = ivec2(${c}, ${h});
+      const ivec2 pads = ivec2(${u}, ${h});
       const float neg_infinity = -3.4e38;
 
       void main() {
@@ -2762,7 +2762,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
           if (hIn >= 0 && hIn < ${t}) {
             for (int w = 0; w < ${o}; w++) {
-              int wIn = wBeg + w * ${u};
+              int wIn = wBeg + w * ${c};
 
               if (wIn >= 0 && wIn < ${n}) {
                 float xVal = getX(batch, hIn, wIn, d1);
@@ -2780,7 +2780,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         float result = curVal;
         setOutput(result);
       }
-    `}};function uV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),c,h=new lV(u);c=n.runWebGLProgram(h,[a,s],"float32");let d=ye({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var cV={kernelName:fu,backendName:"webgl",kernelFunc:uV},hV="return (x >= 0.0) ? x : (exp(x) - 1.0);",dV=`
+    `}};function tV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,c=R.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),u,h=new eV(c);u=n.runWebGLProgram(h,[a,s],"float32");let d=ye({inputs:{x:u},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(u),d}var nV={kernelName:mu,backendName:"webgl",kernelFunc:tV},rV="return (x >= 0.0) ? x : (exp(x) - 1.0);",aV=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -2789,12 +2789,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,pV=Ze({opSnippet:hV,packedOpSnippet:dV}),fV={kernelName:uo,backendName:"webgl",kernelFunc:pV},mV="return (b >= 1.0) ? a : a * (b + 1.0);",AV=`
+`,sV=Ze({opSnippet:rV,packedOpSnippet:aV}),iV={kernelName:uo,backendName:"webgl",kernelFunc:sV},oV="return (b >= 1.0) ? a : a * (b + 1.0);",lV=`
   vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
   return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
-`,yV=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new hc(AV,r.shape,a.shape):new Fl(mV,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},gV={kernelName:Lh,backendName:"webgl",kernelFunc:yV},xV=`
+`,uV=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=J().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new dc(lV,r.shape,a.shape):new Ml(oV,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},cV={kernelName:Wh,backendName:"webgl",kernelFunc:uV},hV=`
   return vec4(equal(a, b));
-`,wV="return float(a == b);",_V=nn({opSnippet:wV,packedOpSnippet:xV,dtype:"bool"}),bV={kernelName:ho,backendName:"webgl",kernelFunc:_V},vV=`
+`,dV="return float(a == b);",pV=nn({opSnippet:dV,packedOpSnippet:hV,dtype:"bool"}),fV={kernelName:ho,backendName:"webgl",kernelFunc:pV},mV=`
   // Error function is calculated approximately with elementary function.
   // See "Handbook of Mathematical Functions with Formulas,
   // Graphs, and Mathematical Tables", Abramowitz and Stegun.
@@ -2809,7 +2809,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
   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));
-`,kV=Ze({opSnippet:vV}),NV={kernelName:co,backendName:"webgl",kernelFunc:kV},xb="return exp(x);",wb=Ze({opSnippet:xb,packedOpSnippet:xb,cpuKernelImpl:kP}),IV={kernelName:ws,backendName:"webgl",kernelFunc:wb};function oA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),ye({inputs:{x:s},backend:r,attrs:{shape:o}})}var SV={kernelName:po,backendName:"webgl",kernelFunc:oA},_b="return exp(x) - 1.0;",TV=Ze({opSnippet:_b,packedOpSnippet:_b,cpuKernelImpl:NP}),CV={kernelName:fo,backendName:"webgl",kernelFunc:TV},bb=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
+`,AV=Ze({opSnippet:mV}),yV={kernelName:co,backendName:"webgl",kernelFunc:AV},w_="return exp(x);",b_=Ze({opSnippet:w_,packedOpSnippet:w_,cpuKernelImpl:AP}),gV={kernelName:ws,backendName:"webgl",kernelFunc:b_};function oA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),ye({inputs:{x:s},backend:r,attrs:{shape:o}})}var xV={kernelName:po,backendName:"webgl",kernelFunc:oA},__="return exp(x) - 1.0;",wV=Ze({opSnippet:__,packedOpSnippet:__,cpuKernelImpl:yP}),bV={kernelName:fo,backendName:"webgl",kernelFunc:wV},v_=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
       const float exponentMultiplier = ${a};
 
       float unaryOpComplex(float real, float expR, float imag, float expI) {
@@ -2842,13 +2842,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ivec2 coords = getOutputCoords();
         setOutput(mulMatDFT(coords[0], coords[1]));
       }
-    `}};function vb(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=ye({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,u=new bb("real",l,t),c=new bb("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(u,h,"float32"),p=n.runWebGLProgram(c,h,"float32"),f=Ua({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=ye({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function EV(e){let{inputs:t,backend:n}=e,{input:r}=t;return vb(r,!1,n)}var RV={kernelName:Wh,backendName:"webgl",kernelFunc:EV},FV=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
+    `}};function k_(e,t,n){let r=n.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=ye({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,c=new v_("real",l,t),u=new v_("imag",l,t),h=[{dataId:r.complexTensorInfos.real.dataId,dtype:r.complexTensorInfos.real.dtype,shape:l},{dataId:r.complexTensorInfos.imag.dataId,dtype:r.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(c,h,"float32"),p=n.runWebGLProgram(u,h,"float32"),f=Ua({inputs:{real:d,imag:p},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p);let m=ye({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(f),m}function _V(e){let{inputs:t,backend:n}=e,{input:r}=t;return k_(r,!1,n)}var vV={kernelName:Bh,backendName:"webgl",kernelFunc:_V},kV=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 lA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new FV(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var MV={kernelName:mu,backendName:"webgl",kernelFunc:lA},$V=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function lA(e){let{backend:t,attrs:n}=e,{shape:r,value:a}=n,{dtype:s}=n;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(r));return i.fill(a),t.makeTensorInfo(r,s,i)}else{let i=new kV(r,a),o=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[],s,o)}}var IV={kernelName:Au,backendName:"webgl",kernelFunc:lA},NV=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];
@@ -2862,7 +2862,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
           setOutput(outputValue);
         }
-    `}},DV={kernelName:mo,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new $V(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},kb="return floor(x);",OV=Ze({opSnippet:kb,packedOpSnippet:kb,cpuKernelImpl:IP}),zV={kernelName:_s,backendName:"webgl",kernelFunc:OV},PV=`
+    `}},SV={kernelName:mo,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,r=t,a=new NV(n.shape);return r.runWebGLProgram(a,[n],n.dtype)}},I_="return floor(x);",TV=Ze({opSnippet:I_,packedOpSnippet:I_,cpuKernelImpl:gP}),CV={kernelName:bs,backendName:"webgl",kernelFunc:TV},EV=`
   float s = sign(a) * sign(b);
   int ia = round(a);
   int ib = round(b);
@@ -2872,7 +2872,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
   } else {
     return NAN;
   }
-`,LV=`
+`,RV=`
   ivec4 ia = round(a);
   ivec4 ib = round(b);
   bvec4 cond = notEqual(ib, ivec4(0));
@@ -2893,7 +2893,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
     result[3] = idiv(ia[3], ib[3], s[3]);
   }
   return vec4(result);
-`,WV=nn({opSnippet:PV,packedOpSnippet:LV,dtype:"int32"}),BV={kernelName:bs,backendName:"webgl",kernelFunc:WV},VV=class{constructor(e){this.variableNames=["A"];let t=fn(),[n,r]=e;this.outputShape=e,this.userCode=`
+`,MV=nn({opSnippet:EV,packedOpSnippet:RV,dtype:"int32"}),FV={kernelName:_s,backendName:"webgl",kernelFunc:MV},$V=class{constructor(e){this.variableNames=["A"];let t=fn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2915,7 +2915,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         setOutput(floor(value * 255.0 + 0.5));
       }
-    `}},UV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=fn(),[n,r]=e;this.outputShape=e,this.userCode=`
+    `}},DV=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=fn(),[n,r]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2949,7 +2949,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
 
         ${t.output} = result;
       }
-    `}},HV={kernelName:td,backendName:"webgl",kernelFunc:jV},$l;function jV(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,u]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],c=[u,l],h=[u,l,s];(o||i)&&($l==null&&($l=document.createElement("canvas").getContext("2d")),$l.canvas.width=l,$l.canvas.height=u,$l.drawImage(a,0,0,l,u),a=$l.canvas);let d=n.makeTensorInfo(c,"int32");n.texData.get(d.dataId).usage=Jn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new UV(h):new VV(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function GV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(c),A=R.computeConv2DInfo(a.shape,s.shape,l,h,u,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=db({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=pb({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let b=i!=null,_=o!=null,x=p==="leakyrelu",I=p?pp(p,!1):null,S=new hb(A,b,I,_,x),T=[a,s];if(i&&T.push(i),o&&T.push(o),x){let M=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));T.push(M),g.push(M)}y=n.runWebGLProgram(S,T,"float32")}let w=ye({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var qV={kernelName:ti,backendName:"webgl",kernelFunc:GV};function XV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=c;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,u,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?pp(d,y):null,w=[a,s],b=i!=null,_=o!=null,x=d==="leakyrelu";if(b&&w.push(i),_&&w.push(o),x){let T=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(T),f.push(T)}let I;y?I=new gb(A,b,g,_,x):I=new yb(A,b,g,_,x);let S=n.runWebGLProgram(I,w,"float32");return f.forEach(T=>n.disposeIntermediateTensorInfo(T)),S}var KV={kernelName:ni,backendName:"webgl",kernelFunc:XV},ZV=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ct(t.length),a=ct(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
+    `}},zV={kernelName:nd,backendName:"webgl",kernelFunc:OV},$l;function OV(e){let{inputs:t,backend:n,attrs:r}=e,{pixels:a}=t,{numChannels:s}=r,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,c]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],u=[c,l],h=[c,l,s];(o||i)&&($l==null&&($l=document.createElement("canvas").getContext("2d")),$l.canvas.width=l,$l.canvas.height=c,$l.drawImage(a,0,0,l,c),a=$l.canvas);let d=n.makeTensorInfo(u,"int32");n.texData.get(d.dataId).usage=Jn.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),a);let p=J().getBool("WEBGL_PACK")?new DV(h):new $V(h),f=n.runWebGLProgram(p,[d],"int32");return n.disposeData(d.dataId),f}function PV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dataFormat:u,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=R.convertConv2DDataFormat(u),A=R.computeConv2DInfo(a.shape,s.shape,l,h,c,d,!1,m),y,g=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))y=p_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else if(J().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)y=f_({x:a,filter:s,convInfo:A,backend:n,bias:i,activation:p,preluActivationWeights:o,leakyreluAlpha:f});else{let b=i!=null,_=o!=null,x=p==="leakyrelu",N=p?fp(p,!1):null,T=new d_(A,b,N,_,x),C=[a,s];if(i&&C.push(i),o&&C.push(o),x){let F=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));C.push(F),g.push(F)}y=n.runWebGLProgram(T,C,"float32")}let w=ye({inputs:{x:y},backend:n,attrs:{shape:A.outShape}});return g.push(y),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var LV={kernelName:ti,backendName:"webgl",kernelFunc:PV};function WV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:c,dilations:u,dimRoundingMode:h,activation:d,leakyreluAlpha:p}=r,f=[],m=u;m==null&&(m=[1,1]),v.assert(R.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let A=R.computeConv2DInfo(a.shape,s.shape,l,m,c,h,!0),y=J().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,g=d?fp(d,y):null,w=[a,s],b=i!=null,_=o!=null,x=d==="leakyrelu";if(b&&w.push(i),_&&w.push(o),x){let C=n.makeTensorInfo([],"float32",v.createScalarValue(p,"float32"));w.push(C),f.push(C)}let N;y?N=new x_(A,b,g,_,x):N=new g_(A,b,g,_,x);let T=n.runWebGLProgram(N,w,"float32");return f.forEach(C=>n.disposeIntermediateTensorInfo(C)),T}var BV={kernelName:ni,backendName:"webgl",kernelFunc:WV},VV=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let r=ut(t.length),a=ut(n.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
         ${r} strides = ${r}(${this.strides});
          void main() {
           ${a} coords = getOutputCoords();
@@ -2960,21 +2960,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
           }
           setOutput(getX(flattenIndex, coords[1]));
         }
-      `}};function YV(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,u,c]=R.prepareAndValidate(r,a),h=ye({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=ye({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/u,u]}}),p=new ZV(i,c,[l,u]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var JV={kernelName:yo,backendName:"webgl",kernelFunc:YV},eU=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ct(this.rank),r=QV(e,2);this.userCode=`
+      `}};function UV(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=a.shape,i=s[s.length-1],[o,l,c,u]=R.prepareAndValidate(r,a),h=ye({inputs:{x:a},backend:n,attrs:{shape:[l,i]}}),d=ye({inputs:{x:r},backend:n,attrs:{shape:[v.sizeFromShape(r.shape)/c,c]}}),p=new VV(i,u,[l,c]),f=n.runWebGLProgram(p,[d,h],d.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(f),m}var jV={kernelName:yo,backendName:"webgl",kernelFunc:UV},GV=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ut(this.rank),r=HV(e,2);this.userCode=`
       void main() {
         ${n} resRC = getOutputCoords();
         setOutput(getA(${r}));
       }
-    `}};function QV(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function tU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],u=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),c=v.sizeFromShape(s.shape),h=[],d=ye({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),p=ye({inputs:{x:s},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});h.push(d),h.push(p);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),b=SP(w,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new eU(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=ye({inputs:{x:A},backend:n,attrs:{shape:u.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var nU={kernelName:Ao,backendName:"webgl",kernelFunc:tU},rU="return float(a > b);",aU=`
+    `}};function HV(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let a=0;a<e.length;a++)a===2?r.push("int(getIndices(resRC.x, resRC.z))"):r.push(`${n[a]}`);return r.join()}function qV(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],c=R.segment_util.collectGatherOpShapeInfo(a,s,l,o),u=v.sizeFromShape(s.shape),h=[],d=ye({inputs:{x:a},backend:n,attrs:{shape:[c.batchSize,c.outerSize,c.dimSize,c.sliceSize]}}),p=ye({inputs:{x:s},backend:n,attrs:{shape:[c.batchSize,u/c.batchSize]}});h.push(d),h.push(p);let f=[c.batchSize,c.outerSize,u/c.batchSize,c.sliceSize];if(n.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let g=n.bufferSync(p),w=n.bufferSync(d),b=xP(w,g,f);return h.forEach(_=>n.disposeIntermediateTensorInfo(_)),n.makeTensorInfo(c.outputShape,b.dtype,b.values)}let m=new GV(d.shape,f),A=n.runWebGLProgram(m,[d,p],d.dtype);h.push(A);let y=ye({inputs:{x:A},backend:n,attrs:{shape:c.outputShape}});return h.forEach(g=>n.disposeIntermediateTensorInfo(g)),y}var XV={kernelName:Ao,backendName:"webgl",kernelFunc:qV},KV="return float(a > b);",ZV=`
   return vec4(greaterThan(a, b));
-`,sU=nn({opSnippet:rU,packedOpSnippet:aU,cpuKernelImpl:TP,dtype:"bool"}),iU={kernelName:go,backendName:"webgl",kernelFunc:sU},oU="return float(a >= b);",lU=`
+`,YV=nn({opSnippet:KV,packedOpSnippet:ZV,cpuKernelImpl:wP,dtype:"bool"}),JV={kernelName:go,backendName:"webgl",kernelFunc:YV},QV="return float(a >= b);",eU=`
   return vec4(greaterThanEqual(a, b));
-`,uU=nn({opSnippet:oU,packedOpSnippet:lU,dtype:"bool"}),cU={kernelName:ks,backendName:"webgl",kernelFunc:uU};function hU(e){let{inputs:t,backend:n}=e,{input:r}=t;return vb(r,!0,n)}var dU={kernelName:Bh,backendName:"webgl",kernelFunc:hU},pU="return float(!isnan(x) && !isinf(x));",fU=Ze({opSnippet:pU,dtype:"bool"}),mU={kernelName:xo,backendName:"webgl",kernelFunc:fU},AU="return float(isinf(x));",yU=Ze({opSnippet:AU,dtype:"bool"}),gU={kernelName:wo,backendName:"webgl",kernelFunc:yU},xU="return float(isnan(x));",wU=Ze({opSnippet:xU,dtype:"bool"}),_U={kernelName:_o,backendName:"webgl",kernelFunc:wU},bU="return float(a < b);",vU=`
+`,tU=nn({opSnippet:QV,packedOpSnippet:eU,dtype:"bool"}),nU={kernelName:ks,backendName:"webgl",kernelFunc:tU};function rU(e){let{inputs:t,backend:n}=e,{input:r}=t;return k_(r,!0,n)}var aU={kernelName:Vh,backendName:"webgl",kernelFunc:rU},sU="return float(!isnan(x) && !isinf(x));",iU=Ze({opSnippet:sU,dtype:"bool"}),oU={kernelName:xo,backendName:"webgl",kernelFunc:iU},lU="return float(isinf(x));",uU=Ze({opSnippet:lU,dtype:"bool"}),cU={kernelName:wo,backendName:"webgl",kernelFunc:uU},hU="return float(isnan(x));",dU=Ze({opSnippet:hU,dtype:"bool"}),pU={kernelName:bo,backendName:"webgl",kernelFunc:dU},fU="return float(a < b);",mU=`
   return vec4(lessThan(a, b));
-`,kU=nn({opSnippet:bU,packedOpSnippet:vU,cpuKernelImpl:CP,dtype:"bool"}),NU={kernelName:bo,backendName:"webgl",kernelFunc:kU},IU="return float(a <= b);",SU=`
+`,AU=nn({opSnippet:fU,packedOpSnippet:mU,cpuKernelImpl:bP,dtype:"bool"}),yU={kernelName:_o,backendName:"webgl",kernelFunc:AU},gU="return float(a <= b);",xU=`
   return vec4(lessThanEqual(a, b));
-`,TU=nn({opSnippet:IU,packedOpSnippet:SU,dtype:"bool"}),CU={kernelName:vo,backendName:"webgl",kernelFunc:TU};function EU(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=EP(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var RU={kernelName:Uh,backendName:"webgl",kernelFunc:EU},FU=`if (x < 0.0) return NAN;
-  return log(x);`,MU=`
+`,wU=nn({opSnippet:gU,packedOpSnippet:xU,dtype:"bool"}),bU={kernelName:vo,backendName:"webgl",kernelFunc:wU};function _U(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=_P(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var vU={kernelName:jh,backendName:"webgl",kernelFunc:_U},kU=`if (x < 0.0) return NAN;
+  return log(x);`,IU=`
   vec4 result = log(x);
   vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
   result.r = isNaN.r == 1.0 ? NAN : result.r;
@@ -2983,16 +2983,16 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
   result.a = isNaN.a == 1.0 ? NAN : result.a;
 
   return result;
-`,$U=Ze({opSnippet:FU,packedOpSnippet:MU,cpuKernelImpl:RP}),DU={kernelName:Ss,backendName:"webgl",kernelFunc:$U},OU="return log(1.0 + x);",zU=Ze({opSnippet:OU}),PU={kernelName:ko,backendName:"webgl",kernelFunc:zU},LU="return float(a >= 1.0 && b >= 1.0);",WU=`
+`,NU=Ze({opSnippet:kU,packedOpSnippet:IU,cpuKernelImpl:vP}),SU={kernelName:Ss,backendName:"webgl",kernelFunc:NU},TU="return log(1.0 + x);",CU=Ze({opSnippet:TU}),EU={kernelName:ko,backendName:"webgl",kernelFunc:CU},RU="return float(a >= 1.0 && b >= 1.0);",MU=`
   return vec4(
     vec4(greaterThanEqual(a, vec4(1.0))) *
     vec4(greaterThanEqual(b, vec4(1.0))));
-`,BU=nn({opSnippet:LU,packedOpSnippet:WU,dtype:"bool"}),VU={kernelName:No,backendName:"webgl",kernelFunc:BU},UU="return float(!(x >= 1.0));",jU=Ze({opSnippet:UU}),HU={kernelName:Au,backendName:"webgl",kernelFunc:jU},GU="return float(a >= 1.0 || b >= 1.0);",qU=`
+`,FU=nn({opSnippet:RU,packedOpSnippet:MU,dtype:"bool"}),$U={kernelName:Io,backendName:"webgl",kernelFunc:FU},DU="return float(!(x >= 1.0));",OU=Ze({opSnippet:DU}),zU={kernelName:yu,backendName:"webgl",kernelFunc:OU},PU="return float(a >= 1.0 || b >= 1.0);",LU=`
   return min(
     vec4(greaterThanEqual(a, vec4(1.0))) +
     vec4(greaterThanEqual(b, vec4(1.0))),
     vec4(1.0));
-`,XU=nn({opSnippet:GU,packedOpSnippet:qU,dtype:"bool"}),KU={kernelName:yu,backendName:"webgl",kernelFunc:XU},ZU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+`,WU=nn({opSnippet:PU,packedOpSnippet:LU,dtype:"bool"}),BU={kernelName:gu,backendName:"webgl",kernelFunc:WU},VU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3011,7 +3011,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         float val = x * ${o};
         setOutput(val);
       }
-    `}},YU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
+    `}},UU=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords.x;
@@ -3073,7 +3073,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         vec4 result = xAtOutputCoords * ${o};
         setOutput(result);
       }
-    `}},JU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,u=J().getBool("WEBGL_PACK_NORMALIZATION")?new YU(a.shape,s,i,o,l):new ZU(a.shape,s,i,o,l);return n.runWebGLProgram(u,[a],a.dtype)},QU={kernelName:gu,backendName:"webgl",kernelFunc:JU},ej=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
+    `}},jU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,c=J().getBool("WEBGL_PACK_NORMALIZATION")?new UU(a.shape,s,i,o,l):new VU(a.shape,s,i,o,l);return n.runWebGLProgram(c,[a],a.dtype)},HU={kernelName:xu,backendName:"webgl",kernelFunc:jU},GU=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3128,14 +3128,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
       }
       setOutput(result);
       }
-    `}},tj=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:c}=r,h=new ej(a.shape,o,l,u,c);return n.runWebGLProgram(h,[a,s,i],a.dtype)},nj={kernelName:jh,backendName:"webgl",kernelFunc:tj};function rj(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,e.dtype,"max",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function Nb(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let x=0;x<w.length;x++)w[x]=a.shape[c[x]];let b=tA(g,a.shape,a.dtype,c,w);p=n.makeTensorInfo(w,a.dtype);let _=n.texData.get(p.dataId);_.values=b}else p=fp(a,c,n);u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("max",u,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,u),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=FP(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let b=n.texData.get(y.dataId);b.values=w}else y=rj(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var aj={kernelName:Ts,backendName:"webgl",kernelFunc:Nb},sj=V_+`
+    `}},qU=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:c,beta:u}=r,h=new GU(a.shape,o,l,c,u);return n.runWebGLProgram(h,[a,s,i],a.dtype)},XU={kernelName:Hh,backendName:"webgl",kernelFunc:qU};function KU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,e.dtype,"max",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function N_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let x=0;x<w.length;x++)w[x]=a.shape[u[x]];let b=tA(g,a.shape,a.dtype,u,w);p=n.makeTensorInfo(w,a.dtype);let _=n.texData.get(p.dataId);_.values=b}else p=mp(a,u,n);c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("max",c,o);let[f,m]=R.computeOutAndReduceShapes(p.shape,c),A=f;i&&(A=R.expandShapeToKeepDim(f,l));let y;if(d){let g=n.texData.get(p.dataId).values,w=kP(g,v.sizeFromShape(m),A,a.dtype);y=n.makeTensorInfo(A,a.dtype);let b=n.texData.get(y.dataId);b.values=w}else y=KU(p,m,A,n);return h&&n.disposeIntermediateTensorInfo(p),y}var ZU={kernelName:Ts,backendName:"webgl",kernelFunc:N_},YU=Ub+`
   return max(a, b);
-`,ij=`
+`,JU=`
   vec4 result = vec4(max(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+dp+`
+  `+pp+`
   return result;
-`,oj=nn({opSnippet:sj,packedOpSnippet:ij,cpuKernelImpl:MP}),lj={kernelName:Cs,backendName:"webgl",kernelFunc:oj};function uj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(R.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=R.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return zn({inputs:{x:a},backend:n});let h=new dc(c,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var cj={kernelName:Es,backendName:"webgl",kernelFunc:uj};function hj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=r,c=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,c,o,u,l),d=new aA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var dj={kernelName:xu,backendName:"webgl",kernelFunc:hj},pj=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
+`,QU=nn({opSnippet:YU,packedOpSnippet:JU,cpuKernelImpl:IP}),ej={kernelName:Cs,backendName:"webgl",kernelFunc:QU};function tj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;kl(a,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,c=1;v.assert(R.eitherStridesOrDilationsAreOne(i,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let u=R.computePool2DInfo(a.shape,s,i,c,o,l);if(u.filterWidth===1&&u.filterHeight===1&&v.arraysEqual(u.inShape,u.outShape))return zn({inputs:{x:a},backend:n});let h=new pc(u,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var nj={kernelName:Es,backendName:"webgl",kernelFunc:tj};function rj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:c}=r,u=[1,1,1],h=R.computePool3DInfo(a.shape,s,i,u,o,c,l),d=new aA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var aj={kernelName:wu,backendName:"webgl",kernelFunc:rj},sj=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${o});
 
       void main() {
@@ -3181,8 +3181,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},fj=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=u-1-e.padInfo.left,p=o*l*u-1;this.userCode=`
-      const ivec3 pads = ivec3(${c}, ${h}, ${d});
+    `}},ij=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,c=e.effectiveFilterWidth,u=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=c-1-e.padInfo.left,p=o*l*c-1;this.userCode=`
+      const ivec3 pads = ivec3(${u}, ${h}, ${d});
 
       void main() {
         ivec5 coords = getOutputCoords();
@@ -3218,7 +3218,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
             }
             int idyR = int(dyR);
 
-            for (int wC = 0; wC < ${u};
+            for (int wC = 0; wC < ${c};
                 wC += ${i}) {
               float dyC = float(dyCCorner + wC) / ${r}.0;
 
@@ -3235,8 +3235,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
               // Get the current value, check it against the value from the
               // position matrix.
               int curPosValue =
-                  wD * ${l} * ${u} +
-                  wR * ${u} + wC;
+                  wD * ${l} * ${c} +
+                  wR * ${c} + wC;
               float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
 
               dotProd += dyValue * mask;
@@ -3245,14 +3245,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function mj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,u,c),p=new aA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new fj(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var Aj={kernelName:Gh,backendName:"webgl",kernelFunc:mj};function yj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;kl([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,u,1,c,h),p=!0,f=new dc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new pj(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var gj={kernelName:Hh,backendName:"webgl",kernelFunc:yj};function xj(e,t,n,r){let a=new dc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new dc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var wj={kernelName:qh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=R.computePool2DInfo(r.shape,a,s,u,i),[h,d]=xj(r,o,c,l);return[h,d]}};function _j(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,"float32","mean",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var bj={kernelName:Rs,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,c=R.getAxesPermutation(u,o),h=c!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,b=new Array(o);for(let I=0;I<b.length;I++)b[I]=r.shape[c[I]];let _=tA(w,r.shape,r.dtype,c,b);f=i.makeTensorInfo(b,r.dtype);let x=i.texData.get(f.dataId);x.values=_}else f=fp(r,c,i);p.push(f),u=R.getInnerMostAxes(u.length,o)}R.assertAxesAreInnerMostDims("sum",u,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,u),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=_j(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function vj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=R.getAxesPermutation(u,o),h=a;c!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:c}}),u=R.getInnerMostAxes(u.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",u,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var kj={kernelName:Fs,backendName:"webgl",kernelFunc:vj},Nj=V_+`
+    `}};function oj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:c,dimRoundingMode:u}=r,h=[1,1,1],d=R.computePool3DInfo(i.shape,o,l,h,c,u),p=new aA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new ij(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var lj={kernelName:qh,backendName:"webgl",kernelFunc:oj};function uj(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;kl([s,i],"maxPoolGrad");let{filterSize:l,strides:c,pad:u,dimRoundingMode:h}=r,d=R.computePool2DInfo(o.shape,l,c,1,u,h),p=!0,f=new pc(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new sj(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var cj={kernelName:Gh,backendName:"webgl",kernelFunc:uj};function hj(e,t,n,r){let a=new pc(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new pc(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var dj={kernelName:Xh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let c=[1,1];v.assert(R.eitherStridesOrDilationsAreOne(s,c),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${c}'`);let u=R.computePool2DInfo(r.shape,a,s,c,i),[h,d]=hj(r,o,u,l);return[h,d]}};function pj(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=vi(i,"float32","mean",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var fj={kernelName:Rs,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),c=l,u=R.getAxesPermutation(c,o),h=u!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,b=new Array(o);for(let N=0;N<b.length;N++)b[N]=r.shape[u[N]];let _=tA(w,r.shape,r.dtype,u,b);f=i.makeTensorInfo(b,r.dtype);let x=i.texData.get(f.dataId);x.values=_}else f=mp(r,u,i);p.push(f),c=R.getInnerMostAxes(c.length,o)}R.assertAxesAreInnerMostDims("sum",c,o);let[m,A]=R.computeOutAndReduceShapes(f.shape,c),y=m;a&&(y=R.expandShapeToKeepDim(m,l));let g=pj(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function mj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),c=l,u=R.getAxesPermutation(c,o),h=a;u!=null&&(h=Nn({inputs:{x:a},backend:n,attrs:{perm:u}}),c=R.getInnerMostAxes(c.length,a.shape.length)),R.assertAxesAreInnerMostDims("min",c,o);let[d,p]=R.computeOutAndReduceShapes(h.shape,c),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=vi(m,m.dtype,"min",n),y;if(i){let g=R.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),u!=null&&n.disposeIntermediateTensorInfo(h),y}var Aj={kernelName:Ms,backendName:"webgl",kernelFunc:mj},yj=Ub+`
   return min(a, b);
-`,Ij=`
+`,gj=`
   vec4 result = vec4(min(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+dp+`
+  `+pp+`
   return result;
-`,Sj=nn({opSnippet:Nj,packedOpSnippet:Ij,cpuKernelImpl:$P}),Tj={kernelName:Ms,backendName:"webgl",kernelFunc:Sj},Cj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let r=e.length,a=ct(r),s=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
+`,xj=nn({opSnippet:yj,packedOpSnippet:gj,cpuKernelImpl:NP}),wj={kernelName:Fs,backendName:"webgl",kernelFunc:xj},bj=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((c,u)=>c[0]+e[u]+c[1]);let r=e.length,a=ut(r),s=t.map(c=>c[0]).join(","),i=t.map((c,u)=>c[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
 
@@ -3281,7 +3281,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${a} coords = outC - start;
         setOutput(getX(${o}));
       }
-    `}},Ej=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=ct(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=mn("rc",r),l=mn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
+    `}},_j=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=ut(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=mn("rc",r),l=mn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=`
         ${a} source = rc;
         if (source < start) {
           source = start * 2 - source - ${h};
@@ -3292,11 +3292,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
       `;d=`
         ${a} rc = outputLoc;
         ${p}
-        result[0] = getChannel(getX(${l.join()}), ${c});
+        result[0] = getChannel(getX(${l.join()}), ${u});
         ${o[r-1]} += 1;
-        if(${u}) {
+        if(${c}) {
           ${p}
-          result[1] = getChannel(getX(${l.join()}), ${c});
+          result[1] = getChannel(getX(${l.join()}), ${u});
         }
       `}else{let p=`
         ${a} source = rc;
@@ -3310,21 +3310,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
       `;d=`
         ${a} rc = outputLoc;
         ${p}
-        result[0] = getChannel(getX(${l.join()}), ${c});
+        result[0] = getChannel(getX(${l.join()}), ${u});
         ${o[r-1]} += 1;
-        if(${u}) {
+        if(${c}) {
           ${p}
-          result[1] = getChannel(getX(${l.join()}), ${c});
+          result[1] = getChannel(getX(${l.join()}), ${u});
         }
         rc = outputLoc;
         ${o[r-2]} += 1;
         if(${o[r-2]} < ${this.outputShape[r-2]}) {
           ${p}
-          result[2] = getChannel(getX(${l.join()}), ${c});
+          result[2] = getChannel(getX(${l.join()}), ${u});
           ${o[r-1]} += 1;
-          if(${u}) {
+          if(${c}) {
             ${p}
-            result[3] = getChannel(getX(${l.join()}), ${c});
+            result[3] = getChannel(getX(${l.join()}), ${u});
           }
         }
       `}this.userCode=`
@@ -3337,13 +3337,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         ${d}
         setOutput(result);
       }
-    `}},Rj=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Ej(r.shape,a,s):new Cj(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},Fj={kernelName:wu,backendName:"webgl",kernelFunc:Rj},Mj=`if (b == 0.0) return NAN;
-  return mod(a, b);`,$j=`
+    `}},vj=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new _j(r.shape,a,s):new bj(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},kj={kernelName:bu,backendName:"webgl",kernelFunc:vj},Ij=`if (b == 0.0) return NAN;
+  return mod(a, b);`,Nj=`
   vec4 result = mod(a, b);
   vec4 isNaN = vec4(equal(b, vec4(0.0)));
-  `+dp+`
+  `+pp+`
   return result;
-`,Dj=nn({opSnippet:Mj,packedOpSnippet:$j}),Oj={kernelName:Io,backendName:"webgl",kernelFunc:Dj},zj=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
+`,Sj=nn({opSnippet:Ij,packedOpSnippet:Nj}),Tj={kernelName:No,backendName:"webgl",kernelFunc:Sj},Cj=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
       uniform float seed;
 
       void main() {
@@ -3365,11 +3365,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,NW=Ze({opSnippet:kW}),IW={kernelNam
         // 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)}}},Pj=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},Ej=`
 if (a == b) {
   return 1.0;
 };
-return a / b;`,Lj=`
+return a / b;`,Rj=`
   // vec4 one = vec4(equal(a, b));
   // return one + (vec4(1.0) - one) * a / b;
   vec4 result = a / b;
@@ -3387,14 +3387,14 @@ return a / b;`,Lj=`
   }
 
   return result;
-`,Ib=nn({opSnippet:Pj,packedOpSnippet:Lj,checkOutOfBounds:!0}),Wj={kernelName:xs,backendName:"webgl",kernelFunc:Ib},Sb="return a - b;",Tb=nn({opSnippet:Sb,packedOpSnippet:Sb,supportsComplex:!0,cpuKernelImpl:VP}),Bj={kernelName:Ys,backendName:"webgl",kernelFunc:Tb};function Cb(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=Nb({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),u=ye({inputs:{x:o},backend:n,attrs:{shape:l}}),c=Tb({inputs:{a,b:u},backend:n}),h=wb({inputs:{x:c},backend:n}),d=rA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=ye({inputs:{x:d},backend:n,attrs:{shape:l}}),f=Ib({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var Vj={kernelName:Ks,backendName:"webgl",kernelFunc:Cb};function Uj(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:Cb({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),u=l.shape[0],c=l.shape[1],h=new zj(u,c,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var jj={kernelName:Xh,backendName:"webgl",kernelFunc:Uj},Eb="return -x;";function Hj(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=OP(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new El(r.shape,Eb):a=new Va(r.shape,Eb),n.runWebGLProgram(a,[r],r.dtype)}var Gj={kernelName:So,backendName:"webgl",kernelFunc:Hj},qj=Wr.nonMaxSuppressionV3Impl;function Xj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,u=n.readSync(a.dataId),c=n.readSync(s.dataId),{selectedIndices:h}=qj(u,c,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var Kj={kernelName:Co,backendName:"webgl",kernelFunc:Xj},Zj=Wr.nonMaxSuppressionV4Impl;function Yj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=Zj(c,h,i,o,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var Jj={kernelName:Eo,backendName:"webgl",kernelFunc:Yj},Qj=Wr.nonMaxSuppressionV5Impl;function eH(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=u,{selectedIndices:A,selectedScores:y}=Qj(c,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var tH={kernelName:Ro,backendName:"webgl",kernelFunc:eH},nH=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
+`,S_=nn({opSnippet:Ej,packedOpSnippet:Rj,checkOutOfBounds:!0}),Mj={kernelName:xs,backendName:"webgl",kernelFunc:S_},T_="return a - b;",C_=nn({opSnippet:T_,packedOpSnippet:T_,supportsComplex:!0,cpuKernelImpl:$P}),Fj={kernelName:Ys,backendName:"webgl",kernelFunc:C_};function E_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=N_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=R.expandShapeToKeepDim(o.shape,i),c=ye({inputs:{x:o},backend:n,attrs:{shape:l}}),u=C_({inputs:{a,b:c},backend:n}),h=b_({inputs:{x:u},backend:n}),d=rA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=ye({inputs:{x:d},backend:n,attrs:{shape:l}}),f=S_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var $j={kernelName:Ks,backendName:"webgl",kernelFunc:E_};function Dj(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:E_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),c=l.shape[0],u=l.shape[1],h=new Cj(c,u,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var Oj={kernelName:Kh,backendName:"webgl",kernelFunc:Dj},R_="return -x;";function zj(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=TP(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return J().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new El(r.shape,R_):a=new Va(r.shape,R_),n.runWebGLProgram(a,[r],r.dtype)}var Pj={kernelName:So,backendName:"webgl",kernelFunc:zj},Lj=Wr.nonMaxSuppressionV3Impl;function Wj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,c=n.readSync(a.dataId),u=n.readSync(s.dataId),{selectedIndices:h}=Lj(c,u,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var Bj={kernelName:Co,backendName:"webgl",kernelFunc:Wj},Vj=Wr.nonMaxSuppressionV4Impl;function Uj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=Vj(u,h,i,o,l,c);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var jj={kernelName:Eo,backendName:"webgl",kernelFunc:Uj},Hj=Wr.nonMaxSuppressionV5Impl;function Gj(e){R.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:c}=r,u=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=c,{selectedIndices:A,selectedScores:y}=Hj(u,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var qj={kernelName:Ro,backendName:"webgl",kernelFunc:Gj},Xj=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)));
       }
-    `}},rH=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),u=new nH(l,s,i,o),c=ye({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(u,[c],a.dtype);n.disposeIntermediateTensorInfo(c);let d=[...a.shape,s],p=ye({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},aH={kernelName:Ds,backendName:"webgl",kernelFunc:rH};function xp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=fc({inputs:{input:r},backend:n}),s=xp({inputs:{x:a},backend:n}),i=gp({inputs:{input:r},backend:n}),o=xp({inputs:{x:i},backend:n}),l=Ua({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return lA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var sH={kernelName:Ko,backendName:"webgl",kernelFunc:xp};function Rb(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=fc({inputs:{input:r},backend:n}),s=Rb({inputs:{x:a},backend:n}),i=gp({inputs:{input:r},backend:n}),o=xp({inputs:{x:i},backend:n}),l=Ua({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return lA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var iH={kernelName:Fo,backendName:"webgl",kernelFunc:Rb};function oH(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return oA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(c=>{let h=oA({inputs:{input:c},backend:n,attrs:{dim:a}});return o.push(h),h}),u=cb({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var lH={kernelName:Mo,backendName:"webgl",kernelFunc:oH},uH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let r=e.length,a=ct(r),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
+    `}},Kj=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),c=new Xj(l,s,i,o),u=ye({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(c,[u],a.dtype);n.disposeIntermediateTensorInfo(u);let d=[...a.shape,s],p=ye({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},Zj={kernelName:Ds,backendName:"webgl",kernelFunc:Kj};function wp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=mc({inputs:{input:r},backend:n}),s=wp({inputs:{x:a},backend:n}),i=xp({inputs:{input:r},backend:n}),o=wp({inputs:{x:i},backend:n}),l=Ua({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return lA({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var Yj={kernelName:Ko,backendName:"webgl",kernelFunc:wp};function M_(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=mc({inputs:{input:r},backend:n}),s=M_({inputs:{x:a},backend:n}),i=xp({inputs:{input:r},backend:n}),o=wp({inputs:{x:i},backend:n}),l=Ua({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return lA({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var Jj={kernelName:Mo,backendName:"webgl",kernelFunc:M_};function Qj(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return oA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(u=>{v.assertShapesMatch(s,u.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===u.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(u=>{let h=oA({inputs:{input:u},backend:n,attrs:{dim:a}});return o.push(h),h}),c=h_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(u=>n.disposeIntermediateTensorInfo(u)),c}var eH={kernelName:Fo,backendName:"webgl",kernelFunc:Qj},tH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,c)=>l[0]+e[c]+l[1]);let r=e.length,a=ut(r),s=t.map(l=>l[0]).join(","),i=t.map((l,c)=>l[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r);if(r===1){this.userCode=`
         int start = ${s};
         int end = ${i};
         uniform float value;
@@ -3421,19 +3421,19 @@ return a / b;`,Lj=`
           setOutput(getX(${o}));
         }
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},cH=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=ct(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=mn("rc",r),l=mn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
-       if(${u}) {
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},nH=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=ut(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=mn("rc",r),l=mn("source",r),c=`${o[r-1]} < ${this.outputShape[r-1]}`,u=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1;
+       if(${c}) {
       `,r===1?"":`}
        rc = outputLoc;
        ${o[r-2]} += 1;
        if(${o[r-2]} < ${this.outputShape[r-2]}) {`,r===1?"":`  ${o[r-1]} += 1;
-         if(${u}) {`],d=r===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let f=0,m=r===1?2:4;f<m;f++)p+=`
+         if(${c}) {`],d=r===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let f=0,m=r===1?2:4;f<m;f++)p+=`
         ${h[f]}
         if (${d}) {
           result[${f}] = float(value);
         } else {
           ${a} source = rc - start;
-          result[${f}] = getChannel(getX(${l.join()}), ${c});
+          result[${f}] = getChannel(getX(${l.join()}), ${u});
         }
       `;p+=r===1?"} ":"}}",this.userCode=`
       const ${a} start = ${a}(${s});
@@ -3446,7 +3446,7 @@ return a / b;`,Lj=`
         ${p}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},Fb=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new cH(a.shape,s,i):new uH(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},hH={kernelName:Os,backendName:"webgl",kernelFunc:Fb},dH=`
+    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}},F_=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new nH(a.shape,s,i):new tH(a.shape,s,i),l=o.getCustomSetupFunc(i);return n.runWebGLProgram(o,[a],a.dtype,l)},rH={kernelName:Os,backendName:"webgl",kernelFunc:F_},aH=`
   if(a < 0.0 && floor(b) < b){
     return NAN;
   }
@@ -3455,7 +3455,7 @@ return a / b;`,Lj=`
   }
   return (round(mod(b, 2.0)) != 1) ?
       pow(abs(a), b) : sign(a) * pow(abs(a), b);
-`,pH=`
+`,sH=`
   // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
   vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
   vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
@@ -3469,11 +3469,11 @@ return a / b;`,Lj=`
   result.a = isExpZero.a ? 1.0 : result.a;
 
   vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
-  `+dp+`
+  `+pp+`
   return result;
-`,fH=nn({opSnippet:dH,packedOpSnippet:pH}),mH={kernelName:zs,backendName:"webgl",kernelFunc:fH};function AH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],u=v.parseAxisParam(s,a.shape),c=u,h=R.getAxesPermutation(c,o),d=a;h!=null&&(d=In({inputs:{x:a},backend:n,attrs:{perm:h}}),c=R.getInnerMostAxes(c.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",c,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=zP(d.shape,d.dtype,f,c);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,c),A=v.sizeFromShape(m),y=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=id(a.dtype),w=vi(y,g,"prod",n);p=ye({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,u);p=ye({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var yH={kernelName:$o,backendName:"webgl",kernelFunc:AH},Mb=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=PP(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},gH={kernelName:_u,backendName:"webgl",kernelFunc:Mb},xH="return 1.0 / x;",wH=Ze({opSnippet:xH}),_H={kernelName:Do,backendName:"webgl",kernelFunc:wH},bH=wr+`
+`,iH=nn({opSnippet:aH,packedOpSnippet:sH}),oH={kernelName:zs,backendName:"webgl",kernelFunc:iH};function lH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],c=v.parseAxisParam(s,a.shape),u=c,h=R.getAxesPermutation(u,o),d=a;h!=null&&(d=Nn({inputs:{x:a},backend:n,attrs:{perm:h}}),u=R.getInnerMostAxes(u.length,o),l.push(d)),R.assertAxesAreInnerMostDims("prod",u,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=CP(d.shape,d.dtype,f,u);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=R.computeOutAndReduceShapes(d.shape,u),A=v.sizeFromShape(m),y=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=od(a.dtype),w=vi(y,g,"prod",n);p=ye({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=R.expandShapeToKeepDim(p.shape,c);p=ye({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var uH={kernelName:$o,backendName:"webgl",kernelFunc:lH},$_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=EP(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},cH={kernelName:_u,backendName:"webgl",kernelFunc:$_},hH="return 1.0 / x;",dH=Ze({opSnippet:hH}),pH={kernelName:Do,backendName:"webgl",kernelFunc:dH},fH=wr+`
   return (x < 0.0) ? 0.0 : x;
-`,vH=`
+`,mH=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3483,9 +3483,9 @@ return a / b;`,Lj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,kH=Ze({opSnippet:bH,packedOpSnippet:vH}),NH={kernelName:Ls,backendName:"webgl",kernelFunc:kH},IH=wr+`
+`,AH=Ze({opSnippet:fH,packedOpSnippet:mH}),yH={kernelName:Ls,backendName:"webgl",kernelFunc:AH},gH=wr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,SH=`
+`,xH=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3495,10 +3495,10 @@ return a / b;`,Lj=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,TH=Ze({opSnippet:IH,packedOpSnippet:SH}),CH={kernelName:Bs,backendName:"webgl",kernelFunc:TH},EH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+`,wH=Ze({opSnippet:gH,packedOpSnippet:xH}),bH={kernelName:Bs,backendName:"webgl",kernelFunc:wH},_H=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
-          ${u[0]/c[0]},
-          ${u[1]/c[1]});
+          ${c[0]/u[0]},
+          ${c[1]/u[1]});
       const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
 
       void main() {
@@ -3528,11 +3528,11 @@ return a / b;`,Lj=`
 
         setOutput(newValue);
       }
-    `}},RH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}},vH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec3 effectiveInputOverOutputRatioRC = vec3(
-          ${u[0]/c[0]},
-          ${u[1]/c[1]},
-          ${u[1]/c[1]});
+          ${c[0]/u[0]},
+          ${c[1]/u[1]},
+          ${c[1]/u[1]});
       const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
                                      ${o}.0);
 
@@ -3605,7 +3605,7 @@ return a / b;`,Lj=`
 
         setOutput(newValue);
       }
-    `}};function FH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new RH(a.shape,l,u,s,i):new EH(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],"float32")}var MH={kernelName:Ws,backendName:"webgl",kernelFunc:FH},$H=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function kH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=J().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new vH(a.shape,l,c,s,i):new _H(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],"float32")}var IH={kernelName:Ws,backendName:"webgl",kernelFunc:kH},NH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3615,8 +3615,8 @@ return a / b;`,Lj=`
 
         float accumulator = 0.0;
 
-        const float heightScale = float(${u});
-        const float widthScale = float(${c});
+        const float heightScale = float(${c});
+        const float widthScale = float(${u});
 
         const float invHeightScale = float(${h});
         const float invWidthScale = float(${d});
@@ -3686,10 +3686,10 @@ return a / b;`,Lj=`
 
         setOutput(accumulator);
       }
-    `}};function DH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new $H(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var OH={kernelName:Yh,backendName:"webgl",kernelFunc:DH},zH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};function SH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new NH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var TH={kernelName:Jh,backendName:"webgl",kernelFunc:SH},CH=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let c=[r&&t>1?i-1:i,r&&n>1?o-1:o],u=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
-          ${u[0]/c[0]},
-          ${u[1]/c[1]});
+          ${c[0]/u[0]},
+          ${c[1]/u[1]});
       const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
 
       void main() {
@@ -3708,7 +3708,7 @@ return a / b;`,Lj=`
 
         setOutput(newValue);
       }
-    `}};function PH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=new zH(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],a.dtype)}var LH={kernelName:bu,backendName:"webgl",kernelFunc:PH},WH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function EH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,c]=o,u=new CH(a.shape,l,c,s,i);return n.runWebGLProgram(u,[a],a.dtype)}var RH={kernelName:vu,backendName:"webgl",kernelFunc:EH},MH=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],c=o[0]/l[0],u=o[1]/l[1],h=1/c,d=1/u,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3718,8 +3718,8 @@ return a / b;`,Lj=`
 
         float accumulator = 0.0;
 
-        const float heightScale = float(${u});
-        const float widthScale = float(${c});
+        const float heightScale = float(${c});
+        const float widthScale = float(${u});
 
         const float invHeightScale = float(${h});
         const float invWidthScale = float(${d});
@@ -3778,17 +3778,17 @@ return a / b;`,Lj=`
 
         setOutput(accumulator);
       }
-    `}};function BH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new WH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var VH={kernelName:Zh,backendName:"webgl",kernelFunc:BH},UH=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=`
+    `}};function FH(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new MH(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var $H={kernelName:Yh,backendName:"webgl",kernelFunc:FH},DH=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
         void main() {
           int coord = getOutputCoords();
           setOutput(getX(${e[0]} - coord - 1));
         }
-      `;return}let r=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>r(o)).join(","),s=ct(n);this.userCode=`
+      `;return}let r=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>r(o)).join(","),s=ut(n);this.userCode=`
       void main() {
         ${s} coords = getOutputCoords();
         setOutput(getX(${a}));
       }
-    `}},jH=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-${n} tensor is not yet supported`);this.outputShape=e;let r=mn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ct(n);n===1?this.userCode=`
+    `}},OH=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=mn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ut(n);n===1?this.userCode=`
         void main(){
           int rc = getOutputCoords();
           vec4 result = vec4(0.);
@@ -3809,14 +3809,14 @@ return a / b;`,Lj=`
             result.g = ${l(r.slice())};
           }
           if(${s}) {
-            result.b = ${u(r.slice())};
+            result.b = ${c(r.slice())};
             if(${a}) {
-              result.a = ${c(r.slice())};
+              result.a = ${u(r.slice())};
             }
           }
           setOutput(result);
         }
-    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function u(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function c(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function HH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return zn({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new jH(a.shape,o):new UH(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var GH={kernelName:Vs,backendName:"webgl",kernelFunc:HH},qH=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
+    `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function c(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function u(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function zH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return zn({inputs:{x:a},backend:n});let l=J().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new OH(a.shape,o):new DH(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var PH={kernelName:Vs,backendName:"webgl",kernelFunc:zH},LH=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],r=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
         vec3 fill = vec3(${t.join(",")});
         float outputValue = fill[coords[3]];`,this.userCode=`
         uniform vec4 params;
@@ -3836,7 +3836,7 @@ return a / b;`,Lj=`
           }
           setOutput(outputValue);
         }
-    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},XH={kernelName:Zo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new qH(r.shape,s),[u,c]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(u,c,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},KH=`
+    `}getCustomSetupFunc(e,t,n,r){return(a,s)=>{this.paramsLoc==null&&(this.paramsLoc=a.getUniformLocationNoThrow(s,"params")),a.gl.uniform4f(this.paramsLoc,e,t,n,r)}}},WH={kernelName:Zo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new LH(r.shape,s),[c,u]=R.getImageCenter(i,r.shape[1],r.shape[2]),h=l.getCustomSetupFunc(c,u,Math.sin(a),Math.cos(a));return o.runWebGLProgram(l,[r],r.dtype,h)}},BH=`
   // OpenGL ES does not support round function.
   // The algorithm is based on banker's rounding.
   float base = floor(x);
@@ -3851,7 +3851,7 @@ return a / b;`,Lj=`
       return base + 1.0;
     }
   }
-`,ZH=Ze({opSnippet:KH}),YH={kernelName:Us,backendName:"webgl",kernelFunc:ZH},JH="return inversesqrt(x);",QH=Ze({opSnippet:JH,cpuKernelImpl:LP}),eG={kernelName:js,backendName:"webgl",kernelFunc:QH},$b=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ct(a.length),l=ct(s.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
+`,VH=Ze({opSnippet:BH}),UH={kernelName:Us,backendName:"webgl",kernelFunc:VH},jH="return inversesqrt(x);",HH=Ze({opSnippet:jH,cpuKernelImpl:RP}),GH={kernelName:js,backendName:"webgl",kernelFunc:HH},D_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=ut(a.length),l=ut(s.length),c="";n===1?c="i":n===2&&(c="i, j");let u=`getIndices(${c})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=`
         ${o} strides = ${o}(${a});
 
         void main() {
@@ -3861,7 +3861,7 @@ return a / b;`,Lj=`
           for (int i = 0; i < ${e}; i++) {
             int flattenedIndex = 0;
             for (int j = 0; j < ${t}; j++) {
-              int index = round(${c});
+              int index = round(${u});
               flattenedIndex += index * ${p};
             }
             if (flattenedIndex == coords[0]) {
@@ -3871,7 +3871,7 @@ return a / b;`,Lj=`
           }
           setOutput(mix(getDefaultValue(), sum, float(found)));
         }
-      `}};function tG(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:u,strides:c,outputSize:h}=R.calculateShapes(s,a,i),d=[h/u,u];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=ye({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=ye({inputs:{x:s},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new $b(l,o,p.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=ye({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var nG={kernelName:zo,backendName:"webgl",kernelFunc:tG},rG=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);r=o.join(),a=l.join()}let s=ct(n);this.userCode=`
+      `}};function qH(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:c,strides:u,outputSize:h}=R.calculateShapes(s,a,i),d=[h/c,c];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=ye({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=ye({inputs:{x:s},backend:n,attrs:{shape:[l,c]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new D_(l,o,p.shape.length,f.shape.length,u,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=ye({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var XH={kernelName:zo,backendName:"webgl",kernelFunc:qH},KH=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let c=0;c<t.length;c++)l.push(`${i[c]}`),c<e&&o.push(`${i[c]}`);r=o.join(),a=l.join()}let s=ut(n);this.userCode=`
       void main() {
         ${s} resRC = getOutputCoords();
         float cVal = getC(${r});
@@ -3881,21 +3881,21 @@ return a / b;`,Lj=`
           setOutput(getB(${a}));
         }
       }
-    `}};function aG(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new rG(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],ar(a.dtype,s.dtype))}var sG={kernelName:Po,backendName:"webgl",kernelFunc:aG},iG=`
+    `}};function ZH(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new KH(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],ar(a.dtype,s.dtype))}var YH={kernelName:Po,backendName:"webgl",kernelFunc:ZH},JH=`
   // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
   // see: https://arxiv.org/abs/1706.02515
   float scaleAlpha = ${R.SELU_SCALEALPHA};
   float scale = ${R.SELU_SCALE};
   return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
-`,oG=Ze({opSnippet:iG}),lG={kernelName:Lo,backendName:"webgl",kernelFunc:oG},uG="return 1.0 / (1.0 + exp(-1.0 * x));",cG=Ze({opSnippet:uG}),hG={kernelName:Gs,backendName:"webgl",kernelFunc:cG},dG=`
+`,QH=Ze({opSnippet:JH}),eG={kernelName:Lo,backendName:"webgl",kernelFunc:QH},tG="return 1.0 / (1.0 + exp(-1.0 * x));",nG=Ze({opSnippet:tG}),rG={kernelName:Gs,backendName:"webgl",kernelFunc:nG},aG=`
   if (isnan(x)) { return 0.0; }
   return sign(x);
-`,pG=Ze({opSnippet:dG}),fG={kernelName:Vo,backendName:"webgl",kernelFunc:pG},mG=q_+`
+`,sG=Ze({opSnippet:aG}),iG={kernelName:Vo,backendName:"webgl",kernelFunc:sG},oG=Xb+`
   return sin(x);
-`,AG=Ze({opSnippet:mG}),yG={kernelName:Hs,backendName:"webgl",kernelFunc:AG},gG=`
+`,lG=Ze({opSnippet:oG}),uG={kernelName:Hs,backendName:"webgl",kernelFunc:lG},cG=`
   float e2x = exp(x);
   return (e2x - 1.0 / e2x) / 2.0;
-`,xG=Ze({opSnippet:gG}),wG={kernelName:Bo,backendName:"webgl",kernelFunc:xG},_G=`
+`,hG=Ze({opSnippet:cG}),dG={kernelName:Bo,backendName:"webgl",kernelFunc:hG},pG=`
   float epsilon = 1.1920928955078125e-7;
   float threshold = log(epsilon) + 2.0;
 
@@ -3915,9 +3915,9 @@ return a / b;`,Lj=`
     result = log(exp_x + 1.0);
   }
   return result;
-`,bG=Ze({opSnippet:_G}),vG={kernelName:Uo,backendName:"webgl",kernelFunc:bG},kG=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let u=[],c=Fb({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(c.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(c.shape,s,o,!1),f=ye({inputs:{x:c},backend:n,attrs:{shape:h}}),m=In({inputs:{x:f},backend:n,attrs:{perm:d}}),A=ye({inputs:{x:m},backend:n,attrs:{shape:p}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},NG={kernelName:vu,backendName:"webgl",kernelFunc:kG};function IG(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:u,strides:c,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new $b(u,l,a.shape.length,s.shape.length,c,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var SG={kernelName:Jh,backendName:"webgl",kernelFunc:IG};function TG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),u=a.shape.length,c=new Array(u).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=pc({inputs:{x:a},backend:n,attrs:{begin:c,size:p}});return c[o]+=d,f})}var CG={kernelName:jo,backendName:"webgl",kernelFunc:TG},EG="return sqrt(x);",RG=Ze({opSnippet:EG}),FG={kernelName:qs,backendName:"webgl",kernelFunc:RG},MG="return x * x;",$G=Ze({opSnippet:MG}),DG={kernelName:ku,backendName:"webgl",kernelFunc:$G},Db="return (a - b) * (a - b);",OG=nn({opSnippet:Db,packedOpSnippet:Db}),zG={kernelName:Zs,backendName:"webgl",kernelFunc:OG};function PG({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=wr+`
+`,fG=Ze({opSnippet:pG}),mG={kernelName:Uo,backendName:"webgl",kernelFunc:fG},AG=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let c=[],u=F_({inputs:{x:a},backend:n,attrs:{paddings:l,constantValue:0}}),h=R.getReshaped(u.shape,s,o,!1),d=R.getPermuted(h.length,s.length,!1),p=R.getReshapedPermuted(u.shape,s,o,!1),f=ye({inputs:{x:u},backend:n,attrs:{shape:h}}),m=Nn({inputs:{x:f},backend:n,attrs:{perm:d}}),A=ye({inputs:{x:m},backend:n,attrs:{shape:p}});return c.push(u),c.push(f),c.push(m),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),A},yG={kernelName:ku,backendName:"webgl",kernelFunc:AG};function gG(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:c,strides:u,outputSize:h}=R.calculateShapes(s,a,o),d=!1,p=new D_(c,l,a.shape.length,s.shape.length,u,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var xG={kernelName:Qh,backendName:"webgl",kernelFunc:gG};function wG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=R.prepareSplitSize(a,s,o),c=a.shape.length,u=new Array(c).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=fc({inputs:{x:a},backend:n,attrs:{begin:u,size:p}});return u[o]+=d,f})}var bG={kernelName:jo,backendName:"webgl",kernelFunc:wG},_G="return sqrt(x);",vG=Ze({opSnippet:_G}),kG={kernelName:qs,backendName:"webgl",kernelFunc:vG},IG="return x * x;",NG=Ze({opSnippet:IG}),SG={kernelName:Iu,backendName:"webgl",kernelFunc:NG},O_="return (a - b) * (a - b);",TG=nn({opSnippet:O_,packedOpSnippet:O_}),CG={kernelName:Zs,backendName:"webgl",kernelFunc:TG};function EG({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=wr+`
     return x > 0.0 ? 1.0 : float(${t.alpha});
-  `,s=new Va(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var LG={kernelName:Ca,backendName:"webgl",kernelFunc:PG},WG=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ct(n.length),s=ct(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,u)=>(o++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
+  `,s=new Va(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var RG={kernelName:Ca,backendName:"webgl",kernelFunc:EG},MG=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=ut(n.length),s=ut(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,c)=>(o++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${o-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
       ${a} begin = ${a}(${e});
       ${a} strides = ${a}(${t});
 
@@ -3925,15 +3925,15 @@ return a / b;`,Lj=`
         ${s} coords = getOutputCoords();
         setOutput(getX(${i}));
       }
-    `}};function BG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=cn.sliceInfo(a.shape,s,i,o,l,u,c,h,d),w=ye({inputs:{x:a},backend:n,attrs:{shape:y}}),b;if(p){let x=pc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});b=ye({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))b=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let x=n.texData.get(w.dataId).values,I=We(w.shape,w.dtype,x),S=BP(g,I,m,f);b=n.makeTensorInfo(g,w.dtype,S.values)}else{let x=new WG(f,m,g);b=n.runWebGLProgram(x,[w],w.dtype)}let _=ye({inputs:{x:b},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(b),_}var VG={kernelName:Ho,backendName:"webgl",kernelFunc:BG},UG="return tan(x);",jG=Ze({opSnippet:UG}),HG={kernelName:Go,backendName:"webgl",kernelFunc:jG},GG=`
+    `}};function FG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:c,ellipsisMask:u,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=cn.sliceInfo(a.shape,s,i,o,l,c,u,h,d),w=ye({inputs:{x:a},backend:n,attrs:{shape:y}}),b;if(p){let x=fc({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});b=ye({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))b=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let x=n.texData.get(w.dataId).values,N=We(w.shape,w.dtype,x),T=FP(g,N,m,f);b=n.makeTensorInfo(g,w.dtype,T.values)}else{let x=new MG(f,m,g);b=n.runWebGLProgram(x,[w],w.dtype)}let _=ye({inputs:{x:b},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(b),_}var $G={kernelName:Ho,backendName:"webgl",kernelFunc:FG},DG="return tan(x);",OG=Ze({opSnippet:DG}),zG={kernelName:Go,backendName:"webgl",kernelFunc:OG},PG=`
   float e2x = exp(-2.0 * abs(x));
   return sign(x) * (1.0 - e2x) / (1.0 + e2x);
-`,qG=Ze({opSnippet:GG}),XG={kernelName:Js,backendName:"webgl",kernelFunc:qG},ZG=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=ct(this.rank),a=KG(e);this.userCode=`
+`,LG=Ze({opSnippet:PG}),WG={kernelName:Js,backendName:"webgl",kernelFunc:LG},VG=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let r=ut(this.rank),a=BG(e);this.userCode=`
       void main() {
         ${r} resRC = getOutputCoords();
         setOutput(getA(${a}));
       }
-    `}};function KG(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function Ob(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(c=>v.decodeString(c)),l=We(a.shape,a.dtype,o),u=UP(l,s);return n.makeTensorInfo(u.shape,u.dtype,u.values)}let i=new ZG(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var YG={kernelName:Ta,backendName:"webgl",kernelFunc:Ob};function JG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,u]=jP(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var QG={kernelName:qo,backendName:"webgl",kernelFunc:JG},eq=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
+    `}};function BG(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;a<e.length;a++)r.push(`imod(${n[a]}, ${e[a]})`);return r.join()}function z_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reps:s}=r;if(a.dtype==="string"){let o=n.readSync(a.dataId).map(u=>v.decodeString(u)),l=We(a.shape,a.dtype,o),c=DP(l,s);return n.makeTensorInfo(c.shape,c.dtype,c.values)}let i=new VG(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var UG={kernelName:Ta,backendName:"webgl",kernelFunc:z_};function jG(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,c]=OP(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(c.shape,c.dtype,c.values)]}var HG={kernelName:qo,backendName:"webgl",kernelFunc:jG},GG=class{constructor(e,t,n,r,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(r){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
             float mapCoord(float outCoord, float len) {
               float inCoord = outCoord;
               if(${o} == 2) {
@@ -4045,7 +4045,7 @@ return a / b;`,Lj=`
               }
               setOutput(outputValue);
             }
-        `}};function tq(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=r,[c,h,d,p]=a.shape,[f,m]=u!=null?u:[h,d],A=[c,f,m,p],y=new eq(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var nq={kernelName:Qh,backendName:"webgl",kernelFunc:tq};function rq(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;kl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=HP(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([u.length],"int32",u)]}var aq={kernelName:ed,backendName:"webgl",kernelFunc:rq};function sq(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],u=new Array(o-1),c=0;for(let m=0;m<o;m++)m!==s&&(u[c++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=pc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=ye({inputs:{x:A},backend:n,attrs:{shape:u}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var iq={kernelName:Xo,backendName:"webgl",kernelFunc:sq},oq=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,h=`
+        `}};function qG(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:c}=r,[u,h,d,p]=a.shape,[f,m]=c!=null?c:[h,d],A=[u,f,m,p],y=new GG(h,d,i,o,l,A);return n.runWebGLProgram(y,[a,s],"float32")}var XG={kernelName:ed,backendName:"webgl",kernelFunc:qG};function KG(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;kl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:c}=zP(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([c.length],"int32",c)]}var ZG={kernelName:td,backendName:"webgl",kernelFunc:KG};function YG(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],c=new Array(o-1),u=0;for(let m=0;m<o;m++)m!==s&&(c[u++]=i.shape[m]);let h=[],d=new Array(o).fill(0),p=i.shape.slice();p[s]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[s]=m;let A=fc({inputs:{x:i},backend:n,attrs:{begin:d,size:p}}),y=ye({inputs:{x:A},backend:n,attrs:{shape:c}});f[m]=y,h.push(A)}return h.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var JG={kernelName:Xo,backendName:"webgl",kernelFunc:YG},QG=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",c=Math.floor(n/4)*4,u=n%4,h=`
         sumValue += dot(values, segFilter);
     `,d="";a%n>0&&(d=`
         if (inIdx < 0 || inIdx >= ${a}) {
@@ -4078,7 +4078,7 @@ return a / b;`,Lj=`
 
         float sumValue = 0.0;
 
-        for (int i = 0; i < ${u}; i += 4) {
+        for (int i = 0; i < ${c}; i += 4) {
           int inIdx = inOffset + i;
           vec4 values = vec4(
             getValue(batch, inIdx),
@@ -4097,8 +4097,8 @@ return a / b;`,Lj=`
           ${h}
         }
 
-        int inIdx = inOffset + ${u};
-        if (${c===1}) {
+        int inIdx = inOffset + ${c};
+        if (${u===1}) {
           vec4 values = vec4(
             getValue(batch, inIdx),
             initializationValue,
@@ -4116,7 +4116,7 @@ return a / b;`,Lj=`
           );
 
           ${h}
-        } else if (${c===2}) {
+        } else if (${u===2}) {
           vec4 values = vec4(
             getValue(batch, inIdx),
             getValue(batch, inIdx + 1),
@@ -4132,7 +4132,7 @@ return a / b;`,Lj=`
           );
 
           ${h}
-        } else if (${c===3}) {
+        } else if (${u===3}) {
           vec4 values = vec4(
             getValue(batch, inIdx),
             getValue(batch, inIdx + 1),
@@ -4151,26 +4151,26 @@ return a / b;`,Lj=`
         }
         setOutput(${l});
       }
-    `}};function lq(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r,o=a.shape.length,l=[],u=0,c=R.getAxesPermutation([u],o),h=a;c!=null&&(h=In({inputs:{x:a},backend:n,attrs:{perm:c}}),l.push(h),u=R.getInnerMostAxes(1,o)[0]);let d=R.segment_util.computeOutShape(h.shape,u,i),p=v.sizeFromShape([h.shape[u]]),f=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=id(a.dtype),A=(b,_,x,I,S)=>{let T=b.shape[0],M=b.shape[1],D=R.segment_util.segOpComputeOptimalWindowSize(M,S),z={windowSize:D,inSize:M,batchSize:T,numSegments:S},B=new oq(z,_),U=n.compileAndRun(B,[b,x],I);if(l.push(U),U.shape[1]===S)return U;let j=Mb({backend:n,attrs:{start:0,stop:S,step:1,dtype:"float32"}}),X=Ob({inputs:{x:j},backend:n,attrs:{reps:[M/D]}});return l.push(j),l.push(X),A(U,_,X,I,S)},y=A(f,"unsortedSegmentSum",s,m,i),g=ye({inputs:{x:y},backend:n,attrs:{shape:d}}),w=g;if(c!=null){l.push(g);let b=R.getUndoAxesPermutation(c);w=In({inputs:{x:w},backend:n,attrs:{perm:b}})}return l.forEach(b=>n.disposeIntermediateTensorInfo(b)),w}var uq={kernelName:Nu,backendName:"webgl",kernelFunc:lq},cq=[QU,nj,BL,UL,GL,KL,YL,eW,nW,aW,lW,cW,pW,AW,vW,xW,IW,EW,TW,$W,OW,PW,VW,KW,YW,rB,sB,uB,dB,bL,AB,IB,TB,wB,FB,$B,EB,zB,WB,UB,HB,qB,ZB,nV,aV,JB,oV,cV,fV,gV,bV,NV,IV,SV,CV,RV,MV,DV,zV,BV,HV,qV,KV,JV,nU,iU,cU,_L,dU,mB,mU,gU,_U,kL,NU,CU,RU,PU,DU,VU,HU,KU,aj,dj,cj,Aj,gj,wj,lj,bj,kj,Tj,Fj,Oj,jj,CL,Gj,Kj,Jj,tH,QW,aH,iH,lH,hH,mH,IL,yH,gH,eB,Wj,_H,CH,NH,RL,MH,OH,LH,VH,GH,XH,YH,eG,nG,sG,lG,hG,fG,yG,wG,qW,Vj,vG,NG,SG,CG,FG,DG,zG,LG,VG,Bj,PL,HG,XG,YG,QG,nq,LL,aq,iq,uq,sH];for(let e of cq)ri(e);var Pn;(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"})(Pn||(Pn={}));var mc;(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"})(mc||(mc={}));var zb;function hq(e){zb=e.wasm.cwrap(ei,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function dq(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s,bias:i,preluActivationWeights:o}=t;if(a.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:h}=r,d=n.dataIdMap.get(a.dataId).id,p=n.dataIdMap.get(s.dataId).id,f=0;if(i!=null){let S=n.dataIdMap.get(i.dataId);if(S.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${S.shape.length}.`);f=S.id}let m=o==null?0:n.dataIdMap.get(o.dataId).id,A=mc[c];if(A==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?a.shape[2]:a.shape[1],g=u?s.shape[1]:s.shape[2],w=a.shape[0],b=n.makeOutput([w,y,g],a.dtype),_=n.dataIdMap.get(b.dataId).id,x=new Uint8Array(new Int32Array(a.shape).buffer),I=new Uint8Array(new Int32Array(s.shape).buffer);return zb(d,x,a.shape.length,p,I,s.shape.length,l,u,A,f,m,h||0,_),b}var pq={kernelName:ei,backendName:"wasm",setupFunc:hq,kernelFunc:dq};function Sn(e){let t;function n(a){t=a.wasm.cwrap(e,null,["number","number"])}function r(a){let{backend:s,inputs:{x:i}}=a,o=s.dataIdMap.get(i.dataId).id,l=s.makeOutput(i.shape,i.dtype),u=s.dataIdMap.get(l.dataId).id;return v.sizeFromShape(l.shape)===0||t(o,u),l}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:r}}var fq=Sn(Yi);function An(e,t,n){let r;function a(i){r=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:c}=l,h=o.dataIdMap.get(u.dataId).id,d=o.dataIdMap.get(c.dataId).id,p=n!=null?n:u.dtype,f=R.assertAndGetBroadcastShape(u.shape,c.shape),m=o.makeOutput(f,p);if(v.sizeFromShape(f)===0)return m;let A=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(c.shape).buffer),g=o.dataIdMap.get(m.dataId).id,w=()=>r(h,A,u.shape.length,d,y,c.shape.length,Pn[u.dtype],g);if(t&&u.dtype==="float32")return w(),m;let b=R.getBroadcastDims(u.shape,f),_=R.getBroadcastDims(c.shape,f),x=b.every((S,T)=>S===T),I=_.every((S,T)=>S===T);if(x&&I)return w(),m;throw new Error(`Broadcasting along outer dims is not yet supported for ${u.dtype} ${e}.`)}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:s}}var mq=!0,Aq=An(Ia,mq),Pb;function yq(e){Pb=e.wasm.cwrap(ls,null,["array","number","number","number"])}function gq(e){let{inputs:t,backend:n}=e,r=n.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(r.shape)===0)return r;let a=t.map(o=>n.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(a).buffer),i=n.dataIdMap.get(r.dataId).id;return Pb(s,a.length,Pn[r.dtype],i),r}var xq={kernelName:ls,backendName:"wasm",setupFunc:yq,kernelFunc:gq};function wp(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype),a=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(r).set(a),r}var wq={kernelName:Ns,backendName:"wasm",kernelFunc:wp},Lb;function _q(e){Lb=e.wasm.cwrap(Qs,null,["number","array","number","number","number","array","number"])}function _p(e){let{inputs:t,backend:n,attrs:r}=e,[a,s]=vq(t.x.shape,r.perm),i=!0;for(let f=0;f<s.length;f++)s[f]!==f&&(i=!1);let o=bq(t.x.shape,r.perm),l={dataId:t.x.dataId,shape:a,dtype:t.x.dtype};if(i){let f=wp({inputs:t,backend:n});return f.shape=o,f}let u=n.makeOutput(o,l.dtype),c=n.dataIdMap.get(l.dataId).id,h=n.dataIdMap.get(u.dataId).id,d=new Uint8Array(new Int32Array(s).buffer),p=new Uint8Array(new Int32Array(l.shape).buffer);return Lb(c,p,l.shape.length,Pn[l.dtype],h,d,s.length),u}function bq(e,t){let n=new Array(e.length);for(let r=0;r<n.length;r++)n[r]=e[t[r]];return n}function vq(e,t){let n=[],r=[];for(let a=0;a<e.length;++a)e[a]!==1&&n.push(e[a]),e[t[a]]!==1&&r.push(t[a]);for(let a=0;a<r.length;++a){let s=-1;for(let i=0;i<r.length;++i)r[i]>=a&&(s===-1||r[s]>r[i])&&(s=i);r[s]=a}return[n,r]}var kq={kernelName:Qs,backendName:"wasm",kernelFunc:_p,setupFunc:_q};function Dl(e,t,n){let r=e.shape,a=e.shape.length,s=v.parseAxisParam(t,r),i=s,o=R.getAxesPermutation(i,a),l=null,u=!1;if(o!=null){let c=new Array(a);for(let d=0;d<c.length;d++)c[d]=r[o[d]];i=R.getInnerMostAxes(i.length,a),l=_p({inputs:{x:e},attrs:{perm:o},backend:n});let h=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==h&&(u=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:u}}var Wb;function Nq(e){Wb=e.wasm.cwrap(us,null,["number","number","number","number","number"])}function Iq(e){let{backend:t,inputs:n,attrs:r}=e,{axis:a}=r,{x:s}=n,i=t.dataIdMap.get(s.dataId).id,o=i,l=s,{transposed:u,axes:c,inputWasTransposed:h}=Dl(s,a,t);if(h){let y=t.dataIdMap.get(u.dataId).id;y!==i&&(l=u,o=y)}let d=l.shape.slice(0,-1),p=t.makeOutput(d,"int32"),f=t.dataIdMap.get(p.dataId).id,m=v.sizeFromShape(p.shape),A=l.shape[c[0]];return Wb(o,Pn[l.dtype],m,A,f),h&&t.disposeData(u.dataId),p}var Sq={kernelName:us,backendName:"wasm",kernelFunc:Iq,setupFunc:Nq},Bb;function Tq(e){Bb=e.wasm.cwrap(cs,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Cq(e){let{inputs:t,attrs:n,backend:r}=e,a=t.x,s=r.dataIdMap.get(a.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,c=R.computePool2DInfo(a.shape,i,o,1,l,u),h=c.filterHeight,d=c.filterWidth,p=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,A=c.padInfo.left,y=c.strideHeight,g=c.strideWidth,w=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"),_=r.dataIdMap.get(b.dataId).id;return Bb(s,a.shape[0],a.shape[1],a.shape[2],h,d,p,f,m,A,y,g,w,_),b}var Eq={kernelName:cs,backendName:"wasm",setupFunc:Tq,kernelFunc:Cq};function _r(e){let{inputs:t,attrs:n}=e,{x:r}=t,{shape:a}=n,s=v.sizeFromShape(r.shape),i=v.inferFromImplicitShape(a,s);return v.assert(s===v.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${r.shape}. 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Provided ${n} not understood: ${JSON.stringify(e)}`)}function F7(e,t){return Wte(e,t,"classWeight")}async function M7(e,t,n,r){if(t!=null||r!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let a=W(()=>{if(e.shape.length===1)return e.clone();if(e.shape.length===2)if(e.shape[1]>1){let o=1;return e.argMax(o)}else{if(e.shape[1]===1)return e.reshape([e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await a.data());Te(a);let i=[];return s.forEach(o=>{if(n[o]==null)throw new Error(`classWeight must contain all classes in the training data. 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Use LayersModel.compile(modelCompileConfig)."),v.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),v.assert(n.epochs!=null&&n.epochs>0&&Number.isInteger(n.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`),v.assert(!r||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),v.assert(n.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. 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t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),s=[],i=()=>{let u=[];for(let p=0;p<this.inputs.length;++p)u.push({key:this.inputs[p],value:n[p]});let c=new Ei(u),h=Cc(this.outputs,c,{training:!0}),d;for(let p=0;p<this.lossFunctions.length;++p){let f=this.lossFunctions[p](r[p],h[p]);a[p]!=null&&(f=Bte(f,a[p]));let m=kt(f);t.push(m),p===0?d=f:d=se(d,f)}for(let p=0;p<this.metricsTensors.length;++p){let f;if(this.outputs.length>1&&p<this.outputs.length)f=t[p];else{let m=this.metricsTensors[p][0],A=this.metricsTensors[p][1];f=kt(m(r[A],h[A]))}Gt(f),s.push(f)}return d=kt(d),this.calculateLosses().forEach(p=>{d=se(d,p)}),d},o=this.collectedTrainableWeights.map(u=>u.read()),l=!0;return[this.optimizer_.minimize(i,l,o)].concat(s)}}makeTestFunction(){this.testFunction=e=>W(()=>{let 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e.metrics)a[s]=Ni(e.metrics[s])}this.compile({loss:r,metrics:a,optimizer:n})}async save(e,t){if(typeof e=="string"){let i=bn.getSaveHandlers(e);if(i.length===0)throw new V(`Cannot find any save handlers for URL '${e}'`);if(i.length>1)throw new V(`Found more than one (${i.length}) save handlers for URL '${e}'`);e=i[0]}if(e.save==null)throw new V("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await bn.encodeWeights(this.getNamedWeights(t)),r=!1,a=null,s={modelTopology:this.toJSON(a,r),format:ene,generatedBy:`TensorFlow.js tfjs-layers v${qA}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){s.trainingConfig=this.getTrainingConfig();let i="optimizer",{data:o,specs:l}=await bn.encodeWeights(await this.optimizer.getWeights(),i);n.specs.push(...l),n.data=bn.concatenateArrayBuffers([n.data,o])}if(this.userDefinedMetadata!=null){let 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};iy.className="ThresholdedReLU";re.registerClass(iy);var oy=class extends Ke{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new QA().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};oy.className="Softmax";re.registerClass(oy);function Vl(e,t,n){if(typeof e=="number")return ki(e,t);if(e.length!==t)throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let r=0;r<t;++r){let a=e[r];if(!OQ(a))throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${a}`)}return e}function Sr(e,t,n,r,a=1){if(e==null)return e;let s=t+(t-1)*(a-1),i;return n==="same"?i=e:i=e-s+1,Math.floor((i+r-1)/r)}function Xp(e,t,n,r){if(e==null)return null;if(r==="valid")e=e*t+Ga([n-t,0]);else if(r==="same")e=e*t;else throw new V(`Unsupport padding mode: ${r}.`);return e}function ly(e,t){return W(()=>(Ct(t),t==="channelsFirst"?at(e,[0,2,3,1]):e))}function rv(e,t){return W(()=>(Ct(t),t==="channelsFirst"?at(e,[0,2,3,4,1]):e))}function hne(e,t,n,r=1,a="valid",s,i=1){return W(()=>{if(s==null&&(s=br()),Ct(s),e.shape.length!==3)throw new V(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new V(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new V(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=at(e,[0,2,1])),a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=md(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Hr(o,n)),o})}function av(e,t,n,r=[1,1],a="valid",s,i,o=null){return W(()=>{if(s==null&&(s=br()),Ct(s),e.rank!==3&&e.rank!==4)throw new V(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new V(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=ly(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Wa.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=at(l,[0,3,1,2])),l})}function dne(e,t,n,r=[1,1,1],a="valid",s,i){return W(()=>{if(s==null&&(s=br()),Ct(s),e.rank!==4&&e.rank!==5)throw new V(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new V(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=rv(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=Yf(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Hr(o,n)),s==="channelsFirst"&&(o=at(o,[0,4,1,2,3])),o})}var uy=class extends Ke{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",uy.verifyArgs(t),this.rank=e,Xt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new De(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Vl(t.kernelSize,e,"kernelSize"),this.strides=Vl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Qn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Ct(this.dataFormat),this.activation=Ka(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=xt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Ut(t.biasConstraint),this.biasRegularizer=wt(t.biasRegularizer),this.activityRegularizer=wt(t.activityRegularizer),this.dilationRate=Vl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new V(`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 V(`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 V(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Ur("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!yA(e.kernelSize,"number",1,3))throw new V(`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:Nt(this.biasInitializer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),biasConstraint:Vt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Fc=class extends uy{constructor(e,t){super(e,t);this.kernel=null,Fc.verifyArgs(t),this.filters=t.filters,Xt(this.filters,"filters"),this.kernelInitializer=xt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Ut(t.kernelConstraint),this.kernelRegularizer=wt(t.kernelRegularizer)}build(e){e=ht(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V(`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 W(()=>{e=Pe(e);let n,r=this.bias==null?null:this.bias.read(),a=U3(this.activation.getClassName());if(a!=null&&this.rank===2)n=av(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,a);else{if(this.rank===1)n=hne(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=av(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=dne(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new De("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=ht(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let a=0;a<n.length;++a){let s=Sr(n[a],this.kernelSize[a],this.padding,this.strides[a],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[a]);t.push(s)}let r=[e[0]];return this.dataFormat==="channelsLast"?(r=r.concat(t),r.push(this.filters)):(r.push(this.filters),r=r.concat(t)),r}getConfig(){let e={filters:this.filters,kernelInitializer:Nt(this.kernelInitializer),kernelRegularizer:dt(this.kernelRegularizer),kernelConstraint:Vt(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 V(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Mc=class extends Fc{constructor(e){super(2,e);Mc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!yA(e.kernelSize,"number",1,2))throw new V(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Mc.className="Conv2D";re.registerClass(Mc);var Kp=class extends Fc{constructor(e){super(3,e);Kp.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 V(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Kp.className="Conv3D";re.registerClass(Kp);var cy=class extends Mc{constructor(e){super(e);if(this.inputSpec=[new Kt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=ht(e),e.length!==4)throw new V("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Kt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return W(()=>{let n=Pe(e);if(n.shape.length!==4)throw new V(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],u=this.kernelSize[0],c=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=Xp(o,h,u,this.padding),f=Xp(l,d,c,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=at(n,[0,2,3,1]));let A=Ad(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=at(A,[0,3,1,2])),this.bias!=null&&(A=Hr(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=ht(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=Xp(t[r],o,s,this.padding),t[a]=Xp(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};cy.className="Conv2DTranspose";re.registerClass(cy);var sv=class extends Fc{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 V("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new V("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 V(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=xt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=wt(t.depthwiseRegularizer),this.depthwiseConstraint=Ut(t.depthwiseConstraint),this.pointwiseInitializer=xt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=wt(t.pointwiseRegularizer),this.pointwiseConstraint=Ut(t.pointwiseConstraint)}build(e){if(e=ht(e),e.length<this.rank+2)throw new V(`Inputs to SeparableConv${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 V(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Kt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return W(()=>{e=Pe(e);let n;if(this.rank===1)throw new De("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=at(e,[0,2,3,1])),n=mm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=at(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Nt(this.depthwiseInitializer),e.pointwiseInitializer=Nt(this.pointwiseInitializer),e.depthwiseRegularizer=dt(this.depthwiseRegularizer),e.pointwiseRegularizer=dt(this.pointwiseRegularizer),e.depthwiseConstraint=Vt(this.depthwiseConstraint),e.pointwiseConstraint=Vt(this.pointwiseConstraint),e}};sv.className="SeparableConv";var hy=class extends sv{constructor(e){super(2,e)}};hy.className="SeparableConv2D";re.registerClass(hy);var Zp=class extends Fc{constructor(e){super(1,e);Zp.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"&&!yA(e.kernelSize,"number",1,1))throw new V(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Zp.className="Conv1D";re.registerClass(Zp);var dy=class extends Ke{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 W(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=Ip(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Ip(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Ip(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Ip(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}};dy.className="Cropping2D";re.registerClass(dy);var py=class extends Ke{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,Ct(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,MQ(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 W(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=at(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return at(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};py.className="UpSampling2D";re.registerClass(py);function pne(e,t,n=[1,1],r="valid",a,s){return W(()=>{a==null&&(a=br()),Ct(a);let i=ly(e,a);if(e.rank!==4)throw new V(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new V(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=cl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=at(i,[0,3,1,2])),i})}var fy=class extends uy{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=xt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Ut(e.depthwiseConstraint),this.depthwiseRegularizer=wt(e.depthwiseRegularizer)}build(e){if(e=ht(e),e.length<4)throw new V(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${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 W(()=>{e=Pe(e);let n=pne(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=ht(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Sr(t,this.kernelSize[0],this.padding,this.strides[0]),s=Sr(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Nt(this.depthwiseInitializer),e.depthwiseRegularizer=dt(this.depthwiseRegularizer),e.depthwiseConstraint=Vt(this.depthwiseRegularizer),e}};fy.className="DepthwiseConv2D";re.registerClass(fy);function iv(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new V("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function ov(e,t,n,r=!1,a,s,i=!1,o=!1){return W(()=>{let l=t.shape.length;if(l<3)throw new V(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(kr(2,l));if(t=at(t,u),s!=null)throw new De("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=hn(a,-1)),a=at(a,u)),r&&(t=Dn(t,0),a!=null&&(a=Dn(a,0)));let c=[],h,d=n,p=t.shape[0],f=or(t),m;a!=null&&(m=or(a));for(let y=0;y<p;++y){let g=f[y],w=W(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let b=W(()=>{let _=m[y],x=$n(_).sub(_),I=w[0].mul(_).add(d[0].mul(x)),S=d.map((T,M)=>w[1][M].mul(_).add(T.mul(x)));return{output:I,newStates:S}});h=b.output,d=b.newStates}o&&c.push(h)}let A;return o&&(A=dn(c,1)),[h,A,d]})}var Gr=class extends Ke{constructor(e){super(e);let t;if(e.cell==null)throw new V("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Yp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new V("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 Kt({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 kr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){zA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return W(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new De("Constants support is not implemented in RNN yet.");zA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Kt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new De("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new V(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Kt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){W(()=>{if(!this.stateful)throw new ca("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new V("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=>Ft([n,r])):this.states_=[Ft([n,this.cell.stateSize])];else if(e==null)Te(this.states_),this.keptStates!=null&&(Te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Ft([n,r])):this.states_[0]=Ft([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):Te(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new V(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Gt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=iv(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Kt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof Nr){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let c=super.apply(o,t);return this.inputSpec=u,c}else return super.apply(e,t)}call(e,t){return W(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new V(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=ov((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],c=o[2];this.stateful&&this.resetStates(c,r);let h=this.returnSequences?u:l;return this.returnState?[h].concat(c):h})}getInitialState(e){return W(()=>{let t=Ft(e.shape);return t=Ce(t,[1,2]),t=vc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?vA(t,[1,n]):t):this.cell.stateSize>1?[vA(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()===Gr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=Ir(r,n);return new e(Object.assign(t,{cell:a}))}};Gr.className="RNN";re.registerClass(Gr);var Ic=class extends Ke{},Jp=class extends Ic{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=xt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=wt(e.kernelRegularizer),this.recurrentRegularizer=wt(e.recurrentRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ht(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 W(()=>{if(e=e,e.length!==2)throw new V(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=jr(P(e,s),this.kernel.read()):a=jr(e,this.kernel.read()),this.bias!=null&&(a=Hr(a,this.bias.read())),i!=null&&(n=P(n,i));let o=se(a,jr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Xa(this.activation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};Jp.className="SimpleRNNCell";re.registerClass(Jp);var my=class extends Gr{constructor(e){e.cell=new Jp(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};my.className="SimpleRNN";re.registerClass(my);var Qp=class extends Ic{constructor(e){super(e);if(this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new V("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ka(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=xt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=wt(e.kernelRegularizer),this.recurrentRegularizer=wt(e.recurrentRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ht(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 W(()=>{if(e=e,e.length!==2)throw new V(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let u=jr(e,this.kernel.read());this.useBias&&(u=Hr(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,s[0]));let c=this.recurrentKernel.read(),[h,d]=Wt(c,[2*this.units,this.units],c.rank-1),p=jr(r,h),[f,m,A]=Wt(u,3,u.rank-1),[y,g]=Wt(p,2,p.rank-1);i=this.recurrentActivation.apply(se(f,y)),o=this.recurrentActivation.apply(se(m,g));let w=jr(P(o,r),d);l=this.activation.apply(se(A,w));let b=se(P(i,r),P(se(1,vt(i)),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:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};Qp.className="GRUCell";re.registerClass(Qp);var Ay=class extends Gr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Qp(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ay.className="GRU";re.registerClass(Ay);var $c=class extends Ic{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ka(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=xt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=wt(e.kernelRegularizer),this.recurrentRegularizer=wt(e.recurrentRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=ht(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends cr{apply(i,o){let l=a.apply([s]),u=new Tp().apply([s]),c=a.apply([s*2]);return Q3(Q3(l,u),c)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return W(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new V(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,c;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let h=jr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=P(r,i[0])),h=se(h,jr(r,this.recurrentKernel.read())),this.useBias&&(h=Hr(h,this.bias.read()));let[d,p,f,m]=Wt(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),u=se(P(l,a),P(o,this.activation.apply(f))),c=this.recurrentActivation.apply(m);let A=P(c,this.activation.apply(u));return[A,A,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Xa(this.activation),recurrentActivation:Xa(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),recurrentInitializer:Nt(this.recurrentInitializer),biasInitializer:Nt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:dt(this.kernelRegularizer),recurrentRegularizer:dt(this.recurrentRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};$c.className="LSTMCell";re.registerClass($c);var yy=class extends Gr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new $c(e),super(e)}call(e,t){return W(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};yy.className="LSTM";re.registerClass(yy);var Yp=class extends Ic{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return W(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){zA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{Si(`RNNCell_${r}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(Ir(a,n));return new e({cells:r})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return PA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}LA(t)}};Yp.className="StackedRNNCells";re.registerClass(Yp);function Za(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>t7(t(),n),i=()=>Nc(s,t,r);return!a||a<=1?Gt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Gt(o.clone()))}var fne=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},lv=class extends Gr{constructor(e){if(e.unroll)throw new De("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new De("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Kt({ndim:5})]}call(e,t){return W(()=>{if(this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new V("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return W(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Ft(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){W(()=>{if(!this.stateful)throw new ca("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ft(a)):this.states_=[Ft(a)];else if(e==null)Te(this.states_),this.keptStates!=null&&(Te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ft(a)):this.states_[0]=Ft(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):Te(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new V(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Gt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],u=e[o?4:3],c=Sr(l,r[0],a,s[0],i[0]),h=Sr(u,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,c,h]:[c,h,n]]}};lv.className="ConvRNN2D";var e0=class extends $c{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Xt(this.filters,"filters"),this.kernelSize=Vl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Xt(o,"kernelSize")),this.strides=Vl(r||1,2,"strides"),this.strides.forEach(o=>Xt(o,"strides")),this.padding=a||"valid",Qn(this.padding),this.dataFormat=s||"channelsLast",Ct(this.dataFormat),this.dilationRate=Vl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Xt(o,"dilationRate"))}build(e){var t;e=ht(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;o=new(t=class extends cr{apply(c,h){let d=l.apply([u]),p=Pr([u]),f=l.apply([u*2]);return NA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return W(()=>{if(e.length!==3)throw new V(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,ae,te)=>!ae||!ae[te]?Y:P(ae[te],Y),u=l(r,o,0),c=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,b,_,x]=Wt(this.kernel.read(),i,g),[I,S,T,M]=this.useBias?Wt(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,w,I,this.padding),c=this.inputConv(c,b,S,this.padding),h=this.inputConv(h,_,T,this.padding),d=this.inputConv(d,x,M,this.padding);let[D,z,B,U]=Wt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,D),m=this.recurrentConv(m,z),A=this.recurrentConv(A,B),y=this.recurrentConv(y,U);let j=this.recurrentActivation.apply(se(u,f)),X=this.recurrentActivation.apply(se(c,m)),H=se(P(X,s),P(j,this.activation.apply(se(h,A)))),ee=P(this.recurrentActivation.apply(se(d,y)),this.activation.apply(H));return[ee,ee,H]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=fne(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=aa(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Hr(a,n,this.dataFormat):a}recurrentConv(e,t){return aa(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};e0.className="ConvLSTM2DCell";re.registerClass(e0);var gy=class extends lv{constructor(e){let t=new e0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};gy.className="ConvLSTM2D";re.registerClass(gy);var t0=class extends Ke{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 W(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Nc(()=>t7(n,this.rate,a,this.seed),()=>n,r)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};t0.className="Dropout";re.registerClass(t0);var xy=class extends t0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};xy.className="SpatialDropout1D";re.registerClass(xy);var wy=class extends Ke{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,Xt(this.units,"units"),this.activation=Ka(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=xt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=xt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Ut(e.kernelConstraint),this.biasConstraint=Ut(e.biasConstraint),this.kernelRegularizer=wt(e.kernelRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.activityRegularizer=wt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=ht(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=ht(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=U3(this.activation.getClassName()),a;return r!=null?a=jr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=jr(n,this.kernel.read()),this.bias!=null&&(a=Hr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Xa(this.activation),useBias:this.useBias,kernelInitializer:Nt(this.kernelInitializer),biasInitializer:Nt(this.biasInitializer),kernelRegularizer:dt(this.kernelRegularizer),biasRegularizer:dt(this.biasRegularizer),activityRegularizer:dt(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),biasConstraint:Vt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};wy.className="Dense";re.registerClass(wy);var _y=class extends Ke{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=ht(e);for(let t of e.slice(1))if(t==null)throw new V(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],Ha(e,1)]}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a<n.rank;++a)r.push(a);r.push(1),n=n.transpose(r)}return LQ(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};_y.className="Flatten";re.registerClass(_y);var by=class extends Ke{constructor(e){super(e);this.supportsMasking=!0,this.activation=Ka(e.activation)}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.activation.apply(n)})}getConfig(){let e={activation:Xa(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};by.className="Activation";re.registerClass(by);var vy=class extends Ke{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return W(()=>(e=Pe(e),zQ(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};vy.className="RepeatVector";re.registerClass(vy);var ky=class extends Ke{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new V("Can only specifiy one unknown dimension.");else a*=l}let i=Ha(e);if(s!==null){if(a===0||i%a!=0)throw new V(n);r[s]=i/a}else if(i!==a)throw new V(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 W(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};ky.className="Reshape";re.registerClass(ky);var Ny=class extends Ke{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=kr(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new Kt({ndim:this.dims.length+1})]}computeOutputShape(e){e=ht(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return at(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Ny.className="Permute";re.registerClass(Ny);var Iy=class extends Ke{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Pe(e),r=-1;return zu(pi(n,this.maskValue),r)}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=zu(pi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Iy.className="Masking";re.registerClass(Iy);var Sy=class extends Ke{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(ft(e.inputLength))}this.inputDim=e.inputDim,Xt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Xt(this.outputDim,"outputDim"),this.embeddingsInitializer=xt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=wt(e.embeddingsRegularizer),this.activityRegularizer=wt(e.activityRegularizer),this.embeddingsConstraint=Ut(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return W(()=>this.maskZero?(e=Pe(e),pi(e,He(e))):null)}computeOutputShape(e){if(e=ht(e),this.inputLength==null)return[...e,this.outputDim];let t=ft(this.inputLength);if(t.length!==e.length-1)throw new V(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new V(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return W(()=>{this.invokeCallHook(e,t);let n=Pe(e);return n.dtype!=="int32"&&(n=bc(n,"int32")),e7(this.embeddings.read(),n.as1D()).reshape(ht(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Nt(this.embeddingsInitializer),embeddingsRegularizer:dt(this.embeddingsRegularizer),activityRegularizer:dt(this.activityRegularizer),embeddingsConstraint:Vt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Sy.className="Embedding";re.registerClass(Sy);var Fi=class extends Ke{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new De}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new V("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[ht(e)]),e=e,e.length<2)throw new V(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let a of e)a!=null&&a[0]!==null&&t.push(a[0]);if(t=ja(t),t.length>1)throw new V(`Can not merge tensors with different batch sizes. 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Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return W(()=>NA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new V("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),r=this.axis<0?n.length+this.axis:this.axis;for(let a of t.slice(1)){if(n[r]==null||a[r]==null){n[r]=null;break}n[r]+=a[r]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new V("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new V("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new V(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return W(()=>{let n=!0;if(t.forEach(s=>{if(s!=null){n=!1;return}}),n)return null;let r=[];for(let s=0;s<e.length;++s)t[s]==null?r.push($n(e[s]).asType("bool")):t[s].rank<e[s].rank?r.push(hn(t[s],-1)):r.push(t[s]);let a=st(r,this.axis);return pd(a,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};My.className="Concatenate";re.registerClass(My);function Dc(e,t){for(;e<0;)e+=t;return e}function mne(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new De("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new De("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return W(()=>{let i;if(r>a){i=r-a;let l=[];for(let u=0;u<i;++u)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let u=0;u<i;++u)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,u=s[1]===t.shape.length-1;o=e.matMul(t,l,u)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let u=[];for(let c=l;c<l+i;++c)u.push(c);o=o.squeeze(u)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var $y=class extends Fi{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new V(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new V(`A \`Dot\` layer must be called on exactly 2 inputs, but 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Dy=class extends Ke{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 W(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Nc(()=>Sp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Dy.className="GaussianNoise";re.registerClass(Dy);var Oy=class extends Ke{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 W(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Nc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Sp(n.shape,1,r))},()=>n,t.training||!1):n})}};Oy.className="GaussianDropout";re.registerClass(Oy);var zy=class extends Ke{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Pe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return W(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Nc(()=>{let r=Pe(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=Pa(Al(n),this.rate);o=bc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,u=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(u)},()=>Pe(e),t.training||!1)}return e})}};zy.className="AlphaDropout";re.registerClass(zy);function Oc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=Q5(e,t,n,r,a,s);else if(e.rank===3)i=ex(e,t,n,r,a,s);else if(e.rank===4)i=tx(e,t,n,r,a,s);else throw new De(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function Ane(e,t,n,r,a=.001){return W(()=>{let s=Nd(e,r),i=s.mean,o=s.variance;return[Oc(e,i,o,n,t,a),i,o]})}function yne(e,t,n,r,a=.001){return W(()=>{let s=Nd(e,r),i=s.mean,o=s.variance,l=[];for(let p of kr(0,e.rank))r.indexOf(p)!==-1?l.push(1):l.push(e.shape[p]);let u=i.reshape(l),c=o.reshape(l),h=t==null?null:t.reshape(l),d=n==null?null:n.reshape(l);return[Oc(e,u,c,d,h,a),i,o]})}function gne(e,t,n,r,a=.001){return v.arraysEqual(r.slice().sort(),kr(0,e.rank-1))?Ane(e,t,n,r,a):yne(e,t,n,r,a)}var Py=class extends Ke{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=xt(e.betaInitializer||"zeros"),this.gammaInitializer=xt(e.gammaInitializer||"ones"),this.movingMeanInitializer=xt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=xt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Ut(e.betaConstraint),this.gammaConstraint=Ut(e.gammaConstraint),this.betaRegularizer=wt(e.betaRegularizer),this.gammaRegularizer=wt(e.gammaRegularizer)}build(e){e=ht(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new V(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Kt({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return W(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=kr(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=ki(1,s);l[o]=a[o];let u=i.slice();u.sort();let c=!v.arraysEqual(u,kr(0,s).slice(0,s-1)),h=()=>{if(c){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return Oc(r,A,y,g,w,this.epsilon)}else return Oc(r,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return h();let[d,p,f]=gne(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{W(()=>{let w=1-g,b=A.read(),_=b.sub(y).mul(w);A.write(b.sub(_))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Nt(this.betaInitializer),gammaInitializer:Nt(this.gammaInitializer),movingMeanInitializer:Nt(this.movingMeanInitializer),movingVarianceInitializer:Nt(this.movingVarianceInitializer),betaRegularizer:dt(this.betaRegularizer),gammaRegularizer:dt(this.gammaRegularizer),betaConstraint:Vt(this.betaConstraint),gammaConstraint:Vt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Py.className="BatchNormalization";re.registerClass(Py);var Ly=class extends Ke{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=xt(e.betaInitializer||"zeros"),this.gammaInitializer=xt(e.gammaInitializer||"ones"),this.betaRegularizer=wt(e.betaRegularizer),this.gammaRegularizer=wt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=ht(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==ja(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Pe(e),r=n.shape,a=r.length;return W(()=>{let s=!0,{mean:i,variance:o}=Nd(n,this.axis,s),l=ki(1,a);for(let f of this.axis)l[f]=r[f];let u=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,c=u(this.gamma.read()),h=u(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),c=c.tile(p),h=h.tile(p),Oc(n,i,o,h,c,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Nt(this.betaInitializer),gammaInitializer:Nt(this.gammaInitializer),betaRegularizer:dt(this.betaRegularizer),gammaRegularizer:dt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Ly.className="LayerNormalization";re.registerClass(Ly);function xne(e,t,n){return W(()=>{if(e.rank!==4)throw new V(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new V("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=br()),n!=="channelsLast"&&n!=="channelsFirst")throw new V(`Unknown data format: ${n}. 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s==="max"?i=qu(e,t,n,o):i=Wu(e,t,n,o),a==="channelsFirst"&&(i=at(i,[0,3,1,2])),i})}function uv(e,t,n,r,a,s){return W(()=>{Ct(a),q3(s),Qn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=br()),s==null&&(s="max"),e=rv(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=lm(e,t,n,o):i=Xf(e,t,n,o),a==="channelsFirst"&&(i=at(i,[0,4,1,2,3])),i})}var cv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new V(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Xt(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new V(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Qn(this.padding),this.inputSpec=[new Kt({ndim:3})]}computeOutputShape(e){e=ht(e);let t=Sr(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return W(()=>{this.invokeCallHook(e,t),e=vc(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return La(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},By=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),n0(e,t,n,r,a,"max")}};By.className="MaxPooling1D";re.registerClass(By);var Vy=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),n0(e,t,n,r,a,"avg")}};Vy.className="AveragePooling1D";re.registerClass(Vy);var hv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new V(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Xt(this.poolSize,"poolSize"),Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),Qn(this.padding),this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){e=ht(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Sr(t,this.poolSize[0],this.padding,this.strides[0]),n=Sr(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return W(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Uy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),n0(e,t,n,r,a,"max")}};Uy.className="MaxPooling2D";re.registerClass(Uy);var jy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),n0(e,t,n,r,a,"avg")}};jy.className="AveragePooling2D";re.registerClass(jy);var dv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new V(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Xt(this.poolSize,"poolSize"),Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),Qn(this.padding),this.inputSpec=[new Kt({ndim:5})]}computeOutputShape(e){e=ht(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Sr(t,this.poolSize[0],this.padding,this.strides[0]),n=Sr(n,this.poolSize[1],this.padding,this.strides[1]),r=Sr(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return W(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Hy=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),uv(e,t,n,r,a,"max")}};Hy.className="MaxPooling3D";re.registerClass(Hy);var Gy=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),uv(e,t,n,r,a,"avg")}};Gy.className="AveragePooling3D";re.registerClass(Gy);var pv=class extends Ke{constructor(e){super(e);this.inputSpec=[new Kt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new De}},qy=class extends pv{constructor(e){super(e||{})}call(e,t){return W(()=>{let n=Pe(e);return kt(n,1)})}};qy.className="GlobalAveragePooling1D";re.registerClass(qy);var Xy=class extends pv{constructor(e){super(e||{})}call(e,t){return W(()=>{let n=Pe(e);return Zn(n,1)})}};Xy.className="GlobalMaxPooling1D";re.registerClass(Xy);var fv=class extends Ke{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new De}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Ky=class extends fv{call(e,t){return W(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?kt(n,[1,2]):kt(n,[2,3])})}};Ky.className="GlobalAveragePooling2D";re.registerClass(Ky);var Zy=class extends fv{call(e,t){return W(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?Zn(n,[1,2]):Zn(n,[2,3])})}};Zy.className="GlobalMaxPooling2D";re.registerClass(Zy);var mv=class extends Ke{constructor(e){super(e);this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let r=t.layer,a=Ir(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},Yy=class extends mv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=ht(e),e.length<3)throw new V(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=ht(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return W(()=>(e=Pe(e),ov((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};Yy.className="TimeDistributed";re.registerClass(Yy);function wne(e){Ii(FQ,"BidirectionalMergeMode",e)}var _ne="concat",Jy=class extends mv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Ir(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=Ir(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?_ne:e.mergeMode,wne(this.mergeMode),e.weights)throw new De("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Tn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=iv(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new V("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let u=n.map(c=>new 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i;return this.mergeMode==="concat"?i=NA([r,a]):this.mergeMode==="sum"?i=se(r,a):this.mergeMode==="ave"?i=P(.5,se(r,a)):this.mergeMode==="mul"?i=P(r,a):this.mergeMode==null&&(i=[r,a]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Si(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Si(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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EA(e)}function cQ(e){return new RA(e)}function hQ(e){return new MA(e)}function dQ(e){return new Cn(e)}function pQ(e){return new Ep(e)}function fQ(e){return new Rp(e)}function mQ(e){return new Mp(e)}function AQ(e){return new Fp(e)}function yQ(e){return new $p(e)}function gQ(e){return new Dp(e)}function xQ(e){return new FA(e)}var 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Kee=0;function h7(){return Kee++}var Op={};function zp(e=""){return e in Op||(Op[e]=0),Op[e]+=1,e+Op[e].toString()}function zA(e){return Array.isArray(e)&&Array.isArray(e[0])}function Pp(e){return e.length===0?[]:Array.isArray(e[0])?e:[e]}function Pe(e){let t;if(Array.isArray(e)){if(e.length!==1)throw new W(`Expected Tensor length to be 1; got ${e.length}`);t=e[0]}else t=e;return t}function ct(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(e.length===1)return e=e,e[0];throw new W(`Expected exactly 1 Shape; got ${e.length}`)}else return e}function Lp(e){let t=0;for(let n of e)n.shape.length===0?t+=1:t+=n.shape.reduce((r,a)=>r*a);return t}var d7="Variable",p7=class{constructor(e,t="float32",n=d7,r=!0,a=null){this.dtype=t==null?"float32":t,this.shape=e.shape,this.id=h7(),n=n==null?d7:n,this.originalName=Y3(n),this.name=J3(this.originalName),this.trainable_=r,this.constraint=a,this.val=Ix(e,this.trainable_,this.name,this.dtype)}read(){return this.assertNotDisposed(),this.val}write(e){return this.assertNotDisposed(),Zee(this.val,e),this.val.id!==e.id&&(this.val.assign(e),this.constraint!=null&&this.val.assign(this.constraint.apply(this.val))),this}dispose(){this.assertNotDisposed(),this.val.dispose()}assertNotDisposed(){if(this.val.isDisposed)throw new Error(`LayersVariable ${this.name} is already disposed.`)}get trainable(){return this.trainable_}set trainable(e){this.trainable_=e,this.val.trainable=e}};function Zee(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function PA(e){return e.map(t=>t.read())}function LA(e){e.forEach(t=>{t[0].write(t[1])})}var 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this.inboundLayers)t!=null?e.push(t.name):e.push(null);return{outboundLayer:this.outboundLayer?this.outboundLayer.name:null,inboundLayers:e,nodeIndices:this.nodeIndices,tensorIndices:this.tensorIndices}}},Jee=0,Ke=class extends re.Serializable{constructor(e={}){super();this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=Jee++,this.activityRegularizer=null,this.inputSpec=null,this.supportsMasking=!1,this._trainableWeights=[],this._nonTrainableWeights=[],this._losses=[],this._updates=[],this._built=!1,this.inboundNodes=[],this.outboundNodes=[];let t=e.name;if(!t){let n=this.getClassName();t=ha(n)+"_"+zp(n)}if(this.name=t,this.trainable_=e.trainable==null?!0:e.trainable,e.inputShape!=null||e.batchInputShape!=null){let n;if(e.batchInputShape!=null)n=e.batchInputShape;else if(e.inputShape!=null){let a=null;e.batchSize!=null&&(a=e.batchSize),n=[a].concat(e.inputShape)}this.batchInputShape=n;let r=e.dtype;r==null&&(r=e.inputDType),r==null&&(r="float32"),this.dtype=r}e.weights!=null?this.initialWeights=e.weights:this.initialWeights=null,this._refCount=null,this.fastWeightInitDuringBuild=!1}static nodeKey(e,t){return e.name+"_ib-"+t.toString()}getNodeAtIndex(e,t){if(this.inboundNodes.length===0)throw new vr(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new W(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return Tn(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return Tn(this.getNodeAtIndex(e,"output").outputTensors)}get input(){if(this.inboundNodes.length>1)throw new ca(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer input" is ill-defined. 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Input received: ${e}`);for(let n=0;n<e.length;n++){let r=e[n],a=t[n];if(a==null)continue;let s=r.rank;if(a.ndim!=null&&s!==a.ndim)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${a.ndim}, found ndim=${s}`);if(a.maxNDim!=null&&s>a.maxNDim)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${a.maxNDim}, found ndim=${s}`);if(a.minNDim!=null&&s<a.minNDim)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected min_ndim=${a.minNDim}, found ndim=${s}.`);if(a.dtype!=null&&r.dtype!==a.dtype)throw new W(`Input ${n} is incompatible with layer ${this.name} : expected dtype=${a.dtype}, found dtype=${r.dtype}.`);if(a.axes){let i=r.shape;for(let o in a.axes){let l=Number(o),c=a.axes[o],u=l>=0?i[l]:i[i.length+l];if(c!=null&&[c,null].indexOf(u)===-1)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${c} but got shape ${i}.`)}}if(a.shape!=null)for(let i=0;i<a.shape.length;++i){let o=a.shape[i],l=r.shape[i];if(o!=null&&l!=null&&o!==l)throw new W(`Input ${n} is incompatible with layer ${this.name}: expected shape=${a.shape}, found shape=${r.shape}.`)}}}call(e,t){return e}invokeCallHook(e,t){this._callHook!=null&&this._callHook(e,t)}setCallHook(e){this._callHook=e}clearCallHook(){this._callHook=null}apply(e,t){t=t||{},this.assertNotDisposed();let n=pt(e),r=!0;for(let s of n)if(!(s instanceof Ir)){r=!1;break}let a=!0;for(let s of n)if(s instanceof Ir){a=!1;break}if(r===a)throw new W("Arguments to apply() must be all SymbolicTensors or all Tensors");return Si(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let s=[];for(let i of pt(e))s.push(i.shape);this.build(Tn(s)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),this._refCount===null&&a&&(this._refCount=1)}if(this.assertInputCompatibility(e),a){let s=this.call(e,t),i=pt(s),o=[];for(let l of i)n.indexOf(l)!==-1&&(l=l.clone()),o.push(l);if(s=Tn(o),this.activityRegularizer!=null)throw new De("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return s}else{let s=Qee(e),i=this.computeOutputShape(s),o,l=ete(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?s[0]:s),i!=null&&i.length>0&&Array.isArray(i[0])?o=i.map((c,u)=>new Ir(l,c,this,pt(e),t,this.name,u)):o=new Ir(l,i,this,pt(e),t,this.name),this.addInboundNode(e,o,null,null,s,i,t),this._refCount++,this.activityRegularizer!=null)throw new De("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return o}})}warnOnIncompatibleInputShape(e){if(this.batchInputShape!=null)if(e.length!==this.batchInputShape.length)console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(e)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);else{let t=!1;this.batchInputShape.forEach((n,r)=>{n!=null&&e[r]!=null&&e[r]!==n&&(t=!0)}),t&&console.warn(`The shape of the input tensor (${JSON.stringify(e)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`)}}get outputShape(){if(this.inboundNodes==null||this.inboundNodes.length===0)throw new ca(`The layer ${this.name} has never been called and thus has no defined output shape.`);let e=[];for(let t of this.inboundNodes){let n=JSON.stringify(t.outputShapes);e.indexOf(n)===-1&&e.push(n)}if(e.length===1){let t=this.inboundNodes[0].outputShapes;return Array.isArray(t)&&Array.isArray(t[0])&&t.length===1?t[0]:t}else throw new ca(`The layer ${this.name} has multiple inbound nodes with different output shapes. Hence the notion of "output shape" is ill-defined for the layer.`)}countParams(){if(!this.built)throw new vr(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return Lp(this.weights)}build(e){this.built=!0}getWeights(e=!1){return PA(e?this.trainableWeights:this.weights)}setWeights(e){L(()=>{let t=this.weights;if(t.length!==e.length)throw new W(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. 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a=M7(e[0],t);n=a.sorted,r=a.recipientMap}else{let a=new Set;for(let s of e){let{sorted:i,recipientMap:o}=M7(s,t);for(let l of i)a.has(l.name)||(n.push(l),a.add(l.name));for(let l in o)r[l]==null&&(r[l]=new Set),o[l].forEach(c=>r[l].add(c))}}return{sorted:n,recipientCounts:Rte(r)}}function Rte(e){let t={};for(let n in e)t[n]=e[n].size;return t}function M7(e,t){let n=new Set,r=[],a={};for(let o of t.names())n.add(o);let s=[],i=[];for(s.push(e);s.length>0;){let o=s[s.length-1];if(n.has(o.name)){s.pop();continue}let l=i[i.length-1]===s.length-1;if(o.inputs.length===0||l)s.pop(),r.push(o),n.add(o.name),l&&i.pop();else{i.push(s.length-1);for(let c of o.inputs)a[c.name]==null&&(a[c.name]=new Set),a[c.name].add(o.name),!n.has(c.name)&&s.push(c)}}return{sorted:r,recipientMap:a}}function Ete(e){let t;if(e.sourceLayer.inboundNodes.length===1)t=e.sourceLayer.output;else{let n=null;for(let r=0;r<e.sourceLayer.inboundNodes.length;++r)for(let a of e.sourceLayer.inboundNodes[r].outputTensors)if(a.id===e.id){n=r;break}t=e.sourceLayer.getOutputAt(n)}return t}var qr=class extends Ke{constructor(e){super({});if(this.containerNodes=new Set,this.name=e.name,this.name==null){let y=this.getClassName().toLowerCase();this.name=zp(y)}if(this.supportsMasking=!1,this.trainable_=!0,Array.isArray(e.inputs)?this.inputs=e.inputs.slice():this.inputs=[e.inputs],Array.isArray(e.outputs)?this.outputs=e.outputs.slice():this.outputs=[e.outputs],ja(this.inputs).length!==this.inputs.length)throw new W(`The list of inputs passed to the model is redundant. 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this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};Bl.className="Sequential";re.registerClass(Bl);function Yte(e){return new da(e)}function Jte(e){return new Bl(e)}function Qte(e,t){return t==null&&(t={}),Kte(e,t)}function i7(e){return m7(e)}function ene(e,t){hr.registerCallbackConstructor(e,t)}var Ln=class extends re.Serializable{getConfig(){return{}}},U7=class extends Ln{apply(e,t=1){return MQ(e,t)}};U7.className="elu";re.registerClass(U7);var j7=class extends Ln{apply(e){return Rd(e)}};j7.className="selu";re.registerClass(j7);var H7=class extends Ln{apply(e){return Lr(e)}};H7.className="relu";re.registerClass(H7);var G7=class extends Ln{apply(e){return L(()=>ml(6,Lr(e)))}};G7.className="relu6";re.registerClass(G7);var q7=class extends Ln{apply(e){return e}};q7.className="linear";re.registerClass(q7);var X7=class extends Ln{apply(e){return 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t.className=e,t.config={},ey(t)}else return e instanceof Ln?e:ey(e)}function ty(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var tv=class extends re.Serializable{},Mc=class extends tv{constructor(e){super();ty(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return L(()=>{let t=Mt([1]);return this.hasL1&&(t=se(t,Ce(O(this.l1,Pt(e))))),this.hasL2&&(t=se(t,Ce(O(this.l2,Ic(e))))),t.asScalar()})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Mc.className="L1L2";re.registerClass(Mc);function tne(e){return ty(e),new Mc({l1:e!=null?e.l1:null,l2:0})}function nne(e){return ty(e),new Mc({l2:e!=null?e.l2:null,l1:0})}var nv={l1l2:"L1L2"};function ht(e){return mA(e)}function rv(e,t={}){return wc(e,re.SerializationMap.getMap().classNameMap,t,"regularizer")}function xt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in nv?nv[e]:e,config:{}};return rv(t)}else return e instanceof tv?e:rv(e)}var ny=class extends Ke{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Pe(e);let n=Lr(e);return this.maxValue!=null&&(n=vn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};ny.className="ReLU";re.registerClass(ny);var ry=class extends Ke{constructor(e){super(e==null?{}:e);this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Pe(e);return Gu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};ry.className="LeakyReLU";re.registerClass(ry);var ay=class extends Ke{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=gt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=xt(e.alphaRegularizer),this.alphaConstraint=Ut(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new W(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=ct(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let r of this.sharedAxes)t[r-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let r=1;r<e.length;++r)n[r]=e[r];this.inputSpec=[new Kt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Pe(e),Zu(e,this.alpha.read())}getConfig(){let e={alphaInitializer:It(this.alphaInitializer),alphaRegularizer:ht(this.alphaRegularizer),alphaConstraint:Vt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};ay.className="PReLU";re.registerClass(ay);var sy=class extends Ke{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new De(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Pe(e);return hl(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};sy.className="ELU";re.registerClass(sy);var iy=class extends Ke{constructor(e){super(e==null?{}:e);this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=Pe(e);return n.mul(vc(n.greater(this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};iy.className="ThresholdedReLU";re.registerClass(iy);var oy=class extends Ke{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new QA().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Pe(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};oy.className="Softmax";re.registerClass(oy);function Vl(e,t,n){if(typeof e=="number")return ki(e,t);if(e.length!==t)throw new W(`The ${n} argument must be an integer or tuple of ${t} integers. 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instead`);if(s==="channelsFirst"&&(e=rt(e,[0,2,1])),a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=Ad(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Hr(o,n)),o})}function sv(e,t,n,r=[1,1],a="valid",s,i,o=null){return L(()=>{if(s==null&&(s=_r()),Ct(s),e.rank!==3&&e.rank!==4)throw new W(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new W(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=ly(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Wa.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=rt(l,[0,3,1,2])),l})}function ane(e,t,n,r=[1,1,1],a="valid",s,i){return L(()=>{if(s==null&&(s=_r()),Ct(s),e.rank!==4&&e.rank!==5)throw new W(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new W(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=av(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=Yf(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Hr(o,n)),s==="channelsFirst"&&(o=rt(o,[0,4,1,2,3])),o})}var uy=class extends Ke{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",uy.verifyArgs(t),this.rank=e,Xt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new De(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Vl(t.kernelSize,e,"kernelSize"),this.strides=Vl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Qn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Ct(this.dataFormat),this.activation=Ka(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=gt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Ut(t.biasConstraint),this.biasRegularizer=xt(t.biasRegularizer),this.activityRegularizer=xt(t.activityRegularizer),this.dilationRate=Vl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new W(`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 W(`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 W(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Ur("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!yA(e.kernelSize,"number",1,3))throw new W(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:Xa(this.activation),useBias:this.useBias,biasInitializer:It(this.biasInitializer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),biasConstraint:Vt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Fc=class extends uy{constructor(e,t){super(e,t);this.kernel=null,Fc.verifyArgs(t),this.filters=t.filters,Xt(this.filters,"filters"),this.kernelInitializer=gt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Ut(t.kernelConstraint),this.kernelRegularizer=xt(t.kernelRegularizer)}build(e){e=ct(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new W(`The channel dimension of the input should be defined. 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Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Kt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return L(()=>{let n=Pe(e);if(n.shape.length!==4)throw new W(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],c=this.kernelSize[0],u=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=Kp(o,h,c,this.padding),f=Kp(l,d,u,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=rt(n,[0,2,3,1]));let A=yd(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=rt(A,[0,3,1,2])),this.bias!=null&&(A=Hr(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=ct(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=Kp(t[r],o,s,this.padding),t[a]=Kp(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};cy.className="Conv2DTranspose";re.registerClass(cy);var iv=class extends Fc{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 W("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new W("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 W(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=gt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=xt(t.depthwiseRegularizer),this.depthwiseConstraint=Ut(t.depthwiseConstraint),this.pointwiseInitializer=gt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=xt(t.pointwiseRegularizer),this.pointwiseConstraint=Ut(t.pointwiseConstraint)}build(e){if(e=ct(e),e.length<this.rank+2)throw new W(`Inputs to SeparableConv${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 W(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",r,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Kt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return L(()=>{e=Pe(e);let n;if(this.rank===1)throw new De("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=rt(e,[0,2,3,1])),n=mm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=rt(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=It(this.depthwiseInitializer),e.pointwiseInitializer=It(this.pointwiseInitializer),e.depthwiseRegularizer=ht(this.depthwiseRegularizer),e.pointwiseRegularizer=ht(this.pointwiseRegularizer),e.depthwiseConstraint=Vt(this.depthwiseConstraint),e.pointwiseConstraint=Vt(this.pointwiseConstraint),e}};iv.className="SeparableConv";var hy=class extends iv{constructor(e){super(2,e)}};hy.className="SeparableConv2D";re.registerClass(hy);var Yp=class extends Fc{constructor(e){super(1,e);Yp.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"&&!yA(e.kernelSize,"number",1,1))throw new W(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Yp.className="Conv1D";re.registerClass(Yp);var dy=class extends Ke{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 L(()=>{if(e=Pe(e),this.dataFormat==="channelsLast"){let n=Sp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Sp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Sp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Sp(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}};dy.className="Cropping2D";re.registerClass(dy);var py=class extends Ke{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,Ct(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,IQ(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 L(()=>{let n=Pe(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=rt(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return rt(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};py.className="UpSampling2D";re.registerClass(py);function sne(e,t,n=[1,1],r="valid",a,s){return L(()=>{a==null&&(a=_r()),Ct(a);let i=ly(e,a);if(e.rank!==4)throw new W(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new W(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=cl(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=rt(i,[0,3,1,2])),i})}var fy=class extends uy{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=gt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Ut(e.depthwiseConstraint),this.depthwiseRegularizer=xt(e.depthwiseRegularizer)}build(e){if(e=ct(e),e.length<4)throw new W(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new W(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${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 L(()=>{e=Pe(e);let n=sne(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Hr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=ct(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=Sr(t,this.kernelSize[0],this.padding,this.strides[0]),s=Sr(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=It(this.depthwiseInitializer),e.depthwiseRegularizer=ht(this.depthwiseRegularizer),e.depthwiseConstraint=Vt(this.depthwiseRegularizer),e}};fy.className="DepthwiseConv2D";re.registerClass(fy);function ov(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new W("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function lv(e,t,n,r=!1,a,s,i=!1,o=!1){return L(()=>{let l=t.shape.length;if(l<3)throw new W(`Input should be at least 3D, but is ${l}D.`);let c=[1,0].concat(kr(2,l));if(t=rt(t,c),s!=null)throw new De("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=hn(a,-1)),a=rt(a,c)),r&&(t=Dn(t,0),a!=null&&(a=Dn(a,0)));let u=[],h,d=n,p=t.shape[0],f=or(t),m;a!=null&&(m=or(a));for(let y=0;y<p;++y){let g=f[y],w=L(()=>e(g,d));if(a==null)h=w[0],d=w[1];else{let b=L(()=>{let _=m[y],x=$n(_).sub(_),N=w[0].mul(_).add(d[0].mul(x)),T=d.map((C,F)=>w[1][F].mul(_).add(C.mul(x)));return{output:N,newStates:T}});h=b.output,d=b.newStates}o&&u.push(h)}let A;return o&&(A=dn(u,1)),[h,A,d]})}var Gr=class extends Ke{constructor(e){super(e);let t;if(e.cell==null)throw new W("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Jp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new W("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 Kt({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 kr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){zA(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return L(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){let t=null;if(this.numConstants!=null)throw new De("Constants support is not implemented in RNN yet.");zA(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Kt({shape:[n,null,...r]});let a=[e[0]].concat(e.slice(2));if(t!=null)throw new De("Constants support is not implemented in RNN yet.");this.cell.build(a);let s;if(Array.isArray(this.cell.stateSize)?s=this.cell.stateSize:s=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),s))throw new W(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Kt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){L(()=>{if(!this.stateful)throw new ca("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new W("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=>Mt([n,r])):this.states_=[Mt([n,this.cell.stateSize])];else if(e==null)Te(this.states_),this.keptStates!=null&&(Te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Mt([n,r])):this.states_[0]=Mt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new W(`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()):Te(this.states_);for(let r=0;r<this.states_.length;++r){let a=e[r],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[r]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(a.shape,i))throw new W(`State ${r} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[r]=a}}this.states_=this.states_.map(r=>Gt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=ov(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Kt({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof Ir){let o=[e].concat(s),l=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=l;let u=super.apply(o,t);return this.inputSpec=c,u}else return super.apply(e,t)}call(e,t){return L(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Pe(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new W(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=lv((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],c=o[1],u=o[2];this.stateful&&this.resetStates(u,r);let h=this.returnSequences?c:l;return this.returnState?[h].concat(u):h})}getInitialState(e){return L(()=>{let t=Mt(e.shape);return t=Ce(t,[1,2]),t=kc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?vA(t,[1,n]):t):this.cell.stateSize>1?[vA(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()===Gr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=Nr(r,n);return new e(Object.assign(t,{cell:a}))}};Gr.className="RNN";re.registerClass(Gr);var Sc=class extends Ke{},Qp=class extends Sc{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,Xt(this.units,"units"),this.activation=Ka(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ct(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 L(()=>{if(e=e,e.length!==2)throw new W(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:r})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=jr(O(e,s),this.kernel.read()):a=jr(e,this.kernel.read()),this.bias!=null&&(a=Hr(a,this.bias.read())),i!=null&&(n=O(n,i));let o=se(a,jr(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Xa(this.activation),useBias:this.useBias,kernelInitializer:It(this.kernelInitializer),recurrentInitializer:It(this.recurrentInitializer),biasInitializer:It(this.biasInitializer),kernelRegularizer:ht(this.kernelRegularizer),recurrentRegularizer:ht(this.recurrentRegularizer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};Qp.className="SimpleRNNCell";re.registerClass(Qp);var my=class extends Gr{constructor(e){e.cell=new Qp(e),super(e)}call(e,t){return L(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};my.className="SimpleRNN";re.registerClass(my);var e0=class extends Sc{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 W("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ka(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ct(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 L(()=>{if(e=e,e.length!==2)throw new W(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=O(e,a[0]));let c=jr(e,this.kernel.read());this.useBias&&(c=Hr(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(r=O(r,s[0]));let u=this.recurrentKernel.read(),[h,d]=Wt(u,[2*this.units,this.units],u.rank-1),p=jr(r,h),[f,m,A]=Wt(c,3,c.rank-1),[y,g]=Wt(p,2,p.rank-1);i=this.recurrentActivation.apply(se(f,y)),o=this.recurrentActivation.apply(se(m,g));let w=jr(O(o,r),d);l=this.activation.apply(se(A,w));let b=se(O(i,r),O(se(1,vt(i)),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:It(this.kernelInitializer),recurrentInitializer:It(this.recurrentInitializer),biasInitializer:It(this.biasInitializer),kernelRegularizer:ht(this.kernelRegularizer),recurrentRegularizer:ht(this.recurrentRegularizer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};e0.className="GRUCell";re.registerClass(e0);var Ay=class extends Gr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new e0(e),super(e)}call(e,t){return L(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ay.className="GRU";re.registerClass(Ay);var Dc=class extends Sc{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Xt(this.units,"units"),this.activation=Ka(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Ka(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=gt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=xt(e.kernelRegularizer),this.recurrentRegularizer=xt(e.recurrentRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.kernelConstraint=Ut(e.kernelConstraint),this.recurrentConstraint=Ut(e.recurrentConstraint),this.biasConstraint=Ut(e.biasConstraint),this.dropout=zl([1,Ga([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=zl([1,Ga([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=ct(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends cr{apply(i,o){let l=a.apply([s]),c=new Cp().apply([s]),u=a.apply([s*2]);return e7(e7(l,c),u)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return L(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new W(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,c,u;0<this.dropout&&this.dropout<1&&(e=O(e,s[0]));let h=jr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(r=O(r,i[0])),h=se(h,jr(r,this.recurrentKernel.read())),this.useBias&&(h=Hr(h,this.bias.read()));let[d,p,f,m]=Wt(h,4,h.rank-1);o=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(p),c=se(O(l,a),O(o,this.activation.apply(f))),u=this.recurrentActivation.apply(m);let A=O(u,this.activation.apply(c));return[A,A,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Xa(this.activation),recurrentActivation:Xa(this.recurrentActivation),useBias:this.useBias,kernelInitializer:It(this.kernelInitializer),recurrentInitializer:It(this.recurrentInitializer),biasInitializer:It(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:ht(this.kernelRegularizer),recurrentRegularizer:ht(this.recurrentRegularizer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),recurrentConstraint:Vt(this.recurrentConstraint),biasConstraint:Vt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Dc.className="LSTMCell";re.registerClass(Dc);var yy=class extends Gr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Dc(e),super(e)}call(e,t){return L(()=>{this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};yy.className="LSTM";re.registerClass(yy);var Jp=class extends Sc{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return L(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=r[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),a.push(s.slice(1))}n=[];for(let i of a.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){zA(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,r)=>{Si(`RNNCell_${r}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(Nr(a,n));return new e({cells:r})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return PA(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],a[s]])}LA(t)}};Jp.className="StackedRNNCells";re.registerClass(Jp);function Za(e){let{ones:t,rate:n,training:r=!1,count:a=1}=e,s=()=>n7(t(),n),i=()=>Nc(s,t,r);return!a||a<=1?Gt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Gt(o.clone()))}var ine=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a<r.length;a++)t.indexOf(r[a])<0&&Object.prototype.propertyIsEnumerable.call(e,r[a])&&(n[r[a]]=e[r[a]]);return n},uv=class extends Gr{constructor(e){if(e.unroll)throw new De("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new De("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Kt({ndim:5})]}call(e,t){return L(()=>{if(this.cell.dropoutMask!=null&&(Te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new W("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return L(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Mt(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){L(()=>{if(!this.stateful)throw new ca("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new W("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Mt(a)):this.states_=[Mt(a)];else if(e==null)Te(this.states_),this.keptStates!=null&&(Te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Mt(a)):this.states_[0]=Mt(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new W(`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()):Te(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new W(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Gt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:r,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],c=e[o?4:3],u=Sr(l,r[0],a,s[0],i[0]),h=Sr(c,r[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[n,u,h]:[u,h,n]]}};uv.className="ConvRNN2D";var t0=class extends Dc{constructor(e){let{filters:t,kernelSize:n,strides:r,padding:a,dataFormat:s,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Xt(this.filters,"filters"),this.kernelSize=Vl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Xt(o,"kernelSize")),this.strides=Vl(r||1,2,"strides"),this.strides.forEach(o=>Xt(o,"strides")),this.padding=a||"valid",Qn(this.padding),this.dataFormat=s||"channelsLast",Ct(this.dataFormat),this.dilationRate=Vl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Xt(o,"dilationRate"))}build(e){var t;e=ct(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new W(`The channel dimension of the input should be defined. Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;o=new(t=class extends cr{apply(u,h){let d=l.apply([c]),p=Pr([c]),f=l.apply([c*2]);return IA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return L(()=>{if(e.length!==3)throw new W(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Za({ones:()=>$n(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(Y,ae,te)=>!ae||!ae[te]?Y:O(ae[te],Y),c=l(r,o,0),u=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Za({ones:()=>$n(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,b,_,x]=Wt(this.kernel.read(),i,g),[N,T,C,F]=this.useBias?Wt(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,w,N,this.padding),u=this.inputConv(u,b,T,this.padding),h=this.inputConv(h,_,C,this.padding),d=this.inputConv(d,x,F,this.padding);let[z,B,V,U]=Wt(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,z),m=this.recurrentConv(m,B),A=this.recurrentConv(A,V),y=this.recurrentConv(y,U);let j=this.recurrentActivation.apply(se(c,f)),X=this.recurrentActivation.apply(se(u,m)),G=se(O(X,s),O(j,this.activation.apply(se(h,A)))),ee=O(this.recurrentActivation.apply(se(d,y)),this.activation.apply(G));return[ee,ee,G]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=ine(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=aa(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Hr(a,n,this.dataFormat):a}recurrentConv(e,t){return aa(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};t0.className="ConvLSTM2DCell";re.registerClass(t0);var gy=class extends uv{constructor(e){let t=new t0(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};gy.className="ConvLSTM2D";re.registerClass(gy);var n0=class extends Ke{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 L(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(0<this.rate&&this.rate<1){let r=t.training==null?!1:t.training,a=this.getNoiseShape(n);return Nc(()=>n7(n,this.rate,a,this.seed),()=>n,r)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};n0.className="Dropout";re.registerClass(n0);var xy=class extends n0{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};xy.className="SpatialDropout1D";re.registerClass(xy);var wy=class extends Ke{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,Xt(this.units,"units"),this.activation=Ka(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=gt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=gt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Ut(e.kernelConstraint),this.biasConstraint=Ut(e.biasConstraint),this.kernelRegularizer=xt(e.kernelRegularizer),this.biasRegularizer=xt(e.biasRegularizer),this.activityRegularizer=xt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=ct(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=ct(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=j3(this.activation.getClassName()),a;return r!=null?a=jr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=jr(n,this.kernel.read()),this.bias!=null&&(a=Hr(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Xa(this.activation),useBias:this.useBias,kernelInitializer:It(this.kernelInitializer),biasInitializer:It(this.biasInitializer),kernelRegularizer:ht(this.kernelRegularizer),biasRegularizer:ht(this.biasRegularizer),activityRegularizer:ht(this.activityRegularizer),kernelConstraint:Vt(this.kernelConstraint),biasConstraint:Vt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};wy.className="Dense";re.registerClass(wy);var by=class extends Ke{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=ct(e);for(let t of e.slice(1))if(t==null)throw new W(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],Ha(e,1)]}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a<n.rank;++a)r.push(a);r.push(1),n=n.transpose(r)}return RQ(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};by.className="Flatten";re.registerClass(by);var _y=class extends Ke{constructor(e){super(e);this.supportsMasking=!0,this.activation=Ka(e.activation)}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.activation.apply(n)})}getConfig(){let e={activation:Xa(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};_y.className="Activation";re.registerClass(_y);var vy=class extends Ke{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return L(()=>(e=Pe(e),CQ(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};vy.className="RepeatVector";re.registerClass(vy);var ky=class extends Ke{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",r=t.slice(),a=1,s=null;for(let o=0;o<r.length;++o){let l=r[o];if(this.isUnknown(l))if(s===null)s=o;else throw new W("Can only specifiy one unknown dimension.");else a*=l}let i=Ha(e);if(s!==null){if(a===0||i%a!=0)throw new W(n);r[s]=i/a}else if(i!==a)throw new W(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 L(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};ky.className="Reshape";re.registerClass(ky);var Iy=class extends Ke{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=kr(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new Kt({ndim:this.dims.length+1})]}computeOutputShape(e){e=ct(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return rt(Pe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Iy.className="Permute";re.registerClass(Iy);var Ny=class extends Ke{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Pe(e),r=-1;return Pu(pi(n,this.maskValue),r)}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e),r=-1,a=!0,s=Pu(pi(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Ny.className="Masking";re.registerClass(Ny);var Sy=class extends Ke{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(pt(e.inputLength))}this.inputDim=e.inputDim,Xt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Xt(this.outputDim,"outputDim"),this.embeddingsInitializer=gt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=xt(e.embeddingsRegularizer),this.activityRegularizer=xt(e.activityRegularizer),this.embeddingsConstraint=Ut(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return L(()=>this.maskZero?(e=Pe(e),pi(e,He(e))):null)}computeOutputShape(e){if(e=ct(e),this.inputLength==null)return[...e,this.outputDim];let t=pt(this.inputLength);if(t.length!==e.length-1)throw new W(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r<t.length;++r){let a=t[r],s=e[r+1];if(a!=null&&s!=null&&a!==s)throw new W(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return L(()=>{this.invokeCallHook(e,t);let n=Pe(e);return n.dtype!=="int32"&&(n=vc(n,"int32")),t7(this.embeddings.read(),n.as1D()).reshape(ct(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:It(this.embeddingsInitializer),embeddingsRegularizer:ht(this.embeddingsRegularizer),activityRegularizer:ht(this.activityRegularizer),embeddingsConstraint:Vt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Sy.className="Embedding";re.registerClass(Sy);var Mi=class extends Ke{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new De}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let r=0;r<t.length;++r){let a=e[e.length-t.length+r],s=t[r];if(a==null||s==null||a<0||s<0)n.push(null);else if(a===1)n.push(s);else if(s===1)n.push(a);else{if(a!==s)throw new W("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(a)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[ct(e)]),e=e,e.length<2)throw new W(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let a of e)a!=null&&a[0]!==null&&t.push(a[0]);if(t=ja(t),t.length>1)throw new W(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let a=1;a<e.length;++a){let s=e[a]==null?null:e[a].slice(1);n=this.computeElementwiseOpOutputShape(n,s)}let r=e.map(a=>a.length);e.indexOf(null)===-1&&ja(r).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return L(()=>{if(e=e,this.reshapeRequired){let n=[],r=e.map(a=>a.rank);if(r.indexOf(null)===-1){let a=Ga(r);for(let s of e){let i=s.rank;for(let o=0;o<a-i;++o)s=kc(s,1);n.push(s)}return this.mergeFunction(n)}else{let a=!1;for(let o of e){let l=o.rank;if(l==null){let c=o.shape,u=c[0],h=c.slice(1).concat([u]),d=o.reshape([u].concat(Ha(c.slice(1))));d=rt(d,[1,0]),d=d.reshape(h),n.push(d),a=!0}else if(l>1){let c=kr(1,l).concat([0]);n.push(rt(o,c)),a=!0}else n.push(o)}let s=this.mergeFunction(n),i=s.rank;if(a){if(i==null){let o=s.shape,l=o.length,c=o[l-1],u=[c].concat(o.slice(0,o.length-1));s=rt(s.reshape([-1,c]),[1,0]).reshape(u)}else if(i>1){let o=[i-1].concat(kr(0,i-1));s=rt(s,o)}}return s}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);t=this.computeElementwiseOpOutputShape(t,a)}let n=[];for(let r of e)r!=null&&r[0]!==null&&n.push(r[0]);return n=ja(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return L(()=>{if(t==null)return null;if(!Array.isArray(t))throw new W("`mask` should be an Array");if(!Array.isArray(e))throw new W("`inputs` should be an Array");if(t.length!==e.length)throw new W(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(r=>r==null))return null;t=t.map(r=>r==null?r:hn(r,0));let n=t[0];for(let r=1;r<t.length-1;++r)n=ir(n,t[r]);return n})}},Ty=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=se(t,e[n]);return t})}};Ty.className="Add";re.registerClass(Ty);var Cy=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=O(t,e[n]);return t})}};Cy.className="Multiply";re.registerClass(Cy);var Ey=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=se(t,e[n]);return O(1/e.length,t)})}};Ey.className="Average";re.registerClass(Ey);var Ry=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=zr(t,e[n]);return t})}};Ry.className="Maximum";re.registerClass(Ry);var My=class extends Mi{constructor(e){super(e)}mergeFunction(e){return L(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=ml(t,e[n]);return t})}};My.className="Minimum";re.registerClass(My);var Fy=class extends Mi{constructor(e){super(e);this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new W("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let r of e)if(r!=null){t=!1;break}if(t)return;let n=[];for(let r=0;r<e.length;++r){let a=e[r].slice();a.splice(this.axis,1);let s=!1;for(let i of n)if(v.arraysEqual(i,a)){s=!0;break}s||n.push(a)}if(n.length>1)throw new W("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return L(()=>IA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new W("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),r=this.axis<0?n.length+this.axis:this.axis;for(let a of t.slice(1)){if(n[r]==null||a[r]==null){n[r]=null;break}n[r]+=a[r]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new W("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new W("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new W(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return L(()=>{let n=!0;if(t.forEach(s=>{if(s!=null){n=!1;return}}),n)return null;let r=[];for(let s=0;s<e.length;++s)t[s]==null?r.push($n(e[s]).asType("bool")):t[s].rank<e[s].rank?r.push(hn(t[s],-1)):r.push(t[s]);let a=at(r,this.axis);return fd(a,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Fy.className="Concatenate";re.registerClass(Fy);function Oc(e,t){for(;e<0;)e+=t;return e}function one(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new De("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new De("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return L(()=>{let i;if(r>a){i=r-a;let l=[];for(let c=0;c<i;++c)l.push(1);t=t.reshape(t.shape.concat(l))}else if(a>r){i=a-r;let l=[];for(let c=0;c<i;++c)l.push(1);e=e.reshape(e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=e.mul(t).sum(s[0]):o=e.transpose([1,0]).mul(t).sum(s[1]);else{let l=s[0]!==e.shape.length-1,c=s[1]===t.shape.length-1;o=e.matMul(t,l,c)}if(i>0){let l;r>a?l=r+a-3:l=r-1;let c=[];for(let u=l;u<l+i;++u)c.push(u);o=o.squeeze(c)}return o.shape.length===1&&(o=o.expandDims(1)),o})}var $y=class extends Mi{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new W(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new W(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],r;return Array.isArray(this.axes)?r=this.axes.map((a,s)=>Oc(a,e[s].shape.length)):r=[Oc(this.axes,t.shape.length),Oc(this.axes,n.shape.length)],this.normalize&&(t=Bp(t,r[0]),n=Bp(n,r[1])),one(t,n,r)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Oc(this.axes,e.length),Oc(this.axes,t.length)],n}computeOutputShape(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);t.splice(r[0],1),n.splice(r[1],1),n.splice(0,1);let a=t.concat(n);return a.length===1&&a.push(1),a}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};$y.className="Dot";re.registerClass($y);var Dy=class extends Ke{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 L(()=>{this.invokeCallHook(e,t);let n=Pe(e);return Nc(()=>Tp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Dy.className="GaussianNoise";re.registerClass(Dy);var Oy=class extends Ke{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 L(()=>{this.invokeCallHook(e,t);let n=Pe(e);return this.rate>0&&this.rate<1?Nc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(Tp(n.shape,1,r))},()=>n,t.training||!1):n})}};Oy.className="GaussianDropout";re.registerClass(Oy);var zy=class extends Ke{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Pe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return L(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Nc(()=>{let r=Pe(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=Pa(Al(n),this.rate);o=vc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(c)},()=>Pe(e),t.training||!1)}return e})}};zy.className="AlphaDropout";re.registerClass(zy);function zc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=ex(e,t,n,r,a,s);else if(e.rank===3)i=tx(e,t,n,r,a,s);else if(e.rank===4)i=nx(e,t,n,r,a,s);else throw new De(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function lne(e,t,n,r,a=.001){return L(()=>{let s=Nd(e,r),i=s.mean,o=s.variance;return[zc(e,i,o,n,t,a),i,o]})}function une(e,t,n,r,a=.001){return L(()=>{let s=Nd(e,r),i=s.mean,o=s.variance,l=[];for(let p of kr(0,e.rank))r.indexOf(p)!==-1?l.push(1):l.push(e.shape[p]);let c=i.reshape(l),u=o.reshape(l),h=t==null?null:t.reshape(l),d=n==null?null:n.reshape(l);return[zc(e,c,u,d,h,a),i,o]})}function cne(e,t,n,r,a=.001){return v.arraysEqual(r.slice().sort(),kr(0,e.rank-1))?lne(e,t,n,r,a):une(e,t,n,r,a)}var Py=class extends Ke{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=gt(e.betaInitializer||"zeros"),this.gammaInitializer=gt(e.gammaInitializer||"ones"),this.movingMeanInitializer=gt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=gt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Ut(e.betaConstraint),this.gammaConstraint=Ut(e.gammaConstraint),this.betaRegularizer=xt(e.betaRegularizer),this.gammaRegularizer=xt(e.gammaRegularizer)}build(e){e=ct(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new W(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Kt({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return L(()=>{let n=t.training==null?!1:t.training,r=Pe(e),a=r.shape,s=a.length,i=kr(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=ki(1,s);l[o]=a[o];let c=i.slice();c.sort();let u=!v.arraysEqual(c,kr(0,s).slice(0,s-1)),h=()=>{if(u){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return zc(r,A,y,g,w,this.epsilon)}else return zc(r,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return h();let[d,p,f]=cne(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{L(()=>{let w=1-g,b=A.read(),_=b.sub(y).mul(w);A.write(b.sub(_))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:It(this.betaInitializer),gammaInitializer:It(this.gammaInitializer),movingMeanInitializer:It(this.movingMeanInitializer),movingVarianceInitializer:It(this.movingVarianceInitializer),betaRegularizer:ht(this.betaRegularizer),gammaRegularizer:ht(this.gammaRegularizer),betaConstraint:Vt(this.betaConstraint),gammaConstraint:Vt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Py.className="BatchNormalization";re.registerClass(Py);var Ly=class extends Ke{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=gt(e.betaInitializer||"zeros"),this.gammaInitializer=gt(e.gammaInitializer||"ones"),this.betaRegularizer=xt(e.betaRegularizer),this.gammaRegularizer=xt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=ct(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==ja(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Pe(e),r=n.shape,a=r.length;return L(()=>{let s=!0,{mean:i,variance:o}=Nd(n,this.axis,s),l=ki(1,a);for(let f of this.axis)l[f]=r[f];let c=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,u=c(this.gamma.read()),h=c(this.beta.read()),d=[],p=[];for(let f=0;f<a;++f)this.axis.indexOf(f)!==-1?(d.push(r[f]),p.push(1)):(d.push(1),p.push(r[f]));return i=i.tile(d),o=o.tile(d),u=u.tile(p),h=h.tile(p),zc(n,i,o,h,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:It(this.betaInitializer),gammaInitializer:It(this.gammaInitializer),betaRegularizer:ht(this.betaRegularizer),gammaRegularizer:ht(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Ly.className="LayerNormalization";re.registerClass(Ly);function hne(e,t,n){return L(()=>{if(e.rank!==4)throw new W(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new W("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=_r()),n!=="channelsLast"&&n!=="channelsFirst")throw new W(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let r;return n==="channelsFirst"?r=[[0,0],[0,0],t[0],t[1]]:r=[[0,0],t[0],t[1],[0,0]],sa(e,r)})}var Wy=class extends Ke{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?_r():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new W(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new W(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new W(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){e=ct(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return L(()=>hne(Pe(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Wy.className="ZeroPadding2D";re.registerClass(Wy);function r0(e,t,n,r,a,s){return L(()=>{Ct(a),X3(s),Qn(r),n==null&&(n=[1,1]),r==null&&(r="valid"),a==null&&(a=_r()),s==null&&(s="max"),e=ly(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=Xu(e,t,n,o):i=Bu(e,t,n,o),a==="channelsFirst"&&(i=rt(i,[0,3,1,2])),i})}function cv(e,t,n,r,a,s){return L(()=>{Ct(a),X3(s),Qn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=_r()),s==null&&(s="max"),e=av(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=lm(e,t,n,o):i=Xf(e,t,n,o),a==="channelsFirst"&&(i=rt(i,[0,4,1,2,3])),i})}var hv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new W(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Xt(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new W(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Qn(this.padding),this.inputSpec=[new Kt({ndim:3})]}computeOutputShape(e){e=ct(e);let t=Sr(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return L(()=>{this.invokeCallHook(e,t),e=kc(Pe(e),2);let n=this.poolingFunction(Pe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return La(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},By=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),r0(e,t,n,r,a,"max")}};By.className="MaxPooling1D";re.registerClass(By);var Vy=class extends hv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),r0(e,t,n,r,a,"avg")}};Vy.className="AveragePooling1D";re.registerClass(Vy);var dv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new W(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Xt(this.poolSize,"poolSize"),Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),Qn(this.padding),this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){e=ct(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Sr(t,this.poolSize[0],this.padding,this.strides[0]),n=Sr(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return L(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Uy=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),r0(e,t,n,r,a,"max")}};Uy.className="MaxPooling2D";re.registerClass(Uy);var jy=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),r0(e,t,n,r,a,"avg")}};jy.className="AveragePooling2D";re.registerClass(jy);var pv=class extends Ke{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new W(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Xt(this.poolSize,"poolSize"),Xt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),Qn(this.padding),this.inputSpec=[new Kt({ndim:5})]}computeOutputShape(e){e=ct(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Sr(t,this.poolSize[0],this.padding,this.strides[0]),n=Sr(n,this.poolSize[1],this.padding,this.strides[1]),r=Sr(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return L(()=>(this.invokeCallHook(e,t),this.poolingFunction(Pe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Hy=class extends pv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),cv(e,t,n,r,a,"max")}};Hy.className="MaxPooling3D";re.registerClass(Hy);var Gy=class extends pv{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Ct(a),Qn(r),cv(e,t,n,r,a,"avg")}};Gy.className="AveragePooling3D";re.registerClass(Gy);var fv=class extends Ke{constructor(e){super(e);this.inputSpec=[new Kt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new De}},qy=class extends fv{constructor(e){super(e||{})}call(e,t){return L(()=>{let n=Pe(e);return kt(n,1)})}};qy.className="GlobalAveragePooling1D";re.registerClass(qy);var Xy=class extends fv{constructor(e){super(e||{})}call(e,t){return L(()=>{let n=Pe(e);return Zn(n,1)})}};Xy.className="GlobalMaxPooling1D";re.registerClass(Xy);var mv=class extends Ke{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Ct(this.dataFormat),this.inputSpec=[new Kt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new De}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Ky=class extends mv{call(e,t){return L(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?kt(n,[1,2]):kt(n,[2,3])})}};Ky.className="GlobalAveragePooling2D";re.registerClass(Ky);var Zy=class extends mv{call(e,t){return L(()=>{let n=Pe(e);return this.dataFormat==="channelsLast"?Zn(n,[1,2]):Zn(n,[2,3])})}};Zy.className="GlobalMaxPooling2D";re.registerClass(Zy);var Av=class extends Ke{constructor(e){super(e);this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let r=t.layer,a=Nr(r,n);delete t.layer;let s={layer:a};return Object.assign(s,t),new e(s)}},Yy=class extends Av{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=ct(e),e.length<3)throw new W(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=ct(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),r=e[1];return[n[0],r].concat(n.slice(1))}call(e,t){return L(()=>(e=Pe(e),lv((n,r)=>[Pe(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};Yy.className="TimeDistributed";re.registerClass(Yy);function dne(e){Ni(kQ,"BidirectionalMergeMode",e)}var pne="concat",Jy=class extends Av{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Nr(n),t.goBackwards=t.goBackwards!==!0;let r={};if(r.className=e.layer.getClassName(),r.config=t,this.backwardLayer=Nr(r),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?pne:e.mergeMode,dne(this.mergeMode),e.weights)throw new De("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,r,a;return this.returnState&&(a=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,r=[n]):this.mergeMode==null?r=[n,n.slice()]:r=[n],this.returnState?this.mergeMode==null?r.concat(a).concat(a.slice()):[n].concat(a).concat(a.slice()):Tn(r)}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=ov(e,n,r,this.numConstants);if(e=a.inputs,n=a.initialState,r=a.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&r==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new W("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let c=n.map(u=>new Kt({shape:u.shape}));this.forwardLayer.stateSpec=c.slice(0,l/2),this.backwardLayer.stateSpec=c.slice(l/2),i.push(...c)}if(r!=null)throw new De("Support for constants in Bidirectional layers is not implemented yet.");let o=s[0]instanceof Ir;for(let l of s)if(l instanceof Ir!==o)throw new W("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(o){let l=[e].concat(s),c=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=c;let h=super.apply(l,t);return this.inputSpec=u,h}else return super.apply(e,t)}call(e,t){return L(()=>{let n=t.initialState,r,a;if(n==null)r=this.forwardLayer.call(e,t),a=this.backwardLayer.call(e,t);else{let o=n.slice(0,n.length/2),l=n.slice(n.length/2);r=this.forwardLayer.call(e,Object.assign(t,{initialState:o})),a=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let s;this.returnState&&(Array.isArray(r)&&(s=r.slice(1).concat(a.slice(1))),r=r[0],a=a[0]),this.returnSequences&&(a=Dn(a,1));let i;return this.mergeMode==="concat"?i=IA([r,a]):this.mergeMode==="sum"?i=se(r,a):this.mergeMode==="ave"?i=O(.5,se(r,a)):this.mergeMode==="mul"?i=O(r,a):this.mergeMode==null&&(i=[r,a]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Si(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Si(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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+        ${n}, and tensor's shape is: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);let a=n===0?0:t.size/n,s=[];L(()=>{t=H(t,[1,n,a]);for(let o=0;o<e.length;++o){let l=o===0?0:r[o-1],c=[0,l,0],u=[1,e[o],a];s[o]=H(Re(t,c,u),this.elementShape)}return s});let i=[];for(let o=0;o<e.length;o++)i[o]=o;this.writeMany(i,s)}},Lc=class{constructor(e,t,n,r=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,e!=null&&e.forEach(a=>{if(n!==a.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${a.dtype}`);dr(t,a.shape,"TensorList shape mismatch: "),Gt(a)}),this.idTensor=ve(0),this.maxNumElements=r,Gt(this.idTensor)}get id(){return this.idTensor.id}copy(){return new Lc([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.id))&&t.dispose()}),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(e,t,n=-1){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(n!==-1&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);dr(e,this.elementShape,"TensorList shape mismatch: ");let r=Pc(this.elementShape,this.tensors,e);return L(()=>{let a=this.tensors.map(s=>H(s,r));return dn(a,0)})}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let n=Pc(this.elementShape,this.tensors,e),r=this.tensors.pop();return dr(r.shape,e,"TensorList shape mismatch: "),H(r,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(dr(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Gt(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${e}`);if(this.maxNumElements!==-1&&e>this.maxNumElements)throw new Error(`TensorListResize input size ${e} is greater maxNumElement ${this.maxNumElements}.`);this.tensors.length=e}getItem(e,t,n){if(n!==this.elementDtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${this.elementDtype}`);if(e<0||e>this.tensors.length)throw new Error(`Trying to access element ${e} in a list with ${this.tensors.length} elements.`);if(this.tensors[e]==null)throw new Error(`element at index ${e} is null.`);dr(this.tensors[e].shape,t,"TensorList shape mismatch: ");let r=Pc(this.elementShape,this.tensors,t);return H(this.tensors[e],r)}setItem(e,t){if(t.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t.dtype}, but list elements ${this.elementDtype}`);if(e<0||this.maxNumElements!==-1&&e>=this.maxNumElements)throw new Error(`Trying to set element ${e} in a list with max ${this.maxNumElements} elements.`);dr(this.elementShape,t.shape,"TensorList shape mismatch: "),Gt(t),this.tensors[e]=t}gather(e,t,n){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);dr(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());let r=Pc(this.elementShape,this.tensors,n);return e.length===0?xr([],[0].concat(r)):L(()=>{let a=e.map(s=>H(this.tensors[s],r));return dn(a,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);dr(this.elementShape,t,"TensorList shape mismatch: ");let n=Pc(this.elementShape,this.tensors,t);return this.size()===0?xr([],[0].concat(n)):L(()=>{let r=this.tensors.map(a=>H(a,n));return at(r,0)})}};function sre(e,t,n){let r=e.dtype;if(e.shape.length<1)throw new Error(`Tensor must be at least a vector, but saw shape: ${e.shape}`);if(e.dtype!==n)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${n}`);let a=e.shape.slice(1);dr(a,t,"TensorList shape mismatch: ");let s=or(e);return new Lc(s,t,r)}function ire(e,t,n){return new Lc([],e,t,n)}function ore(e,t,n,r){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let a=Math.max(...t);if(r!=null&&r!==-1&&a>=r)throw new Error(`Max index must be < array size (${a}  vs. ${r})`);let s=new Lc([],n,e.dtype,r),i=or(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function lre(e,t,n){let r=0,a=t.map(u=>(r+=u,r));if(r!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to
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r=k("size",e,t,n),a=k("dtype",e,t,n),s=k("elementShape",e,t,n),i=k("dynamicSize",e,t,n),o=k("clearAfterRead",e,t,n),l=k("identicalElementShapes",e,t,n),u=k("name",e,t,n),c=new dre(u,a,r,s,l,i,o);return n.addTensorArray(c),[c.idTensor,ve(1)]}case"TensorArrayWriteV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.write(a,s),[i.idTensor]}case"TensorArrayReadV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,s)]}case"TensorArrayScatterV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.scatter(a,s),[i.idTensor]}case"TensorArrayConcatV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),s=k("dtype",e,t,n);return[a.concat(s)]}case"TensorArraySplitV3":{let 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r=k("elementShape",e,t,n),a=k("elementDType",e,t,n),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,n),o=fre(r,a,i);return n.addTensorList(o),[o.idTensor]}case"TensorListGather":{let r=k("tensorListId",e,t,n),a=k("indices",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,i,s)]}case"TensorListStack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=k("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,s,i)]}case"TensorListFromTensor":{let r=k("tensor",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=pre(r,a,s);return n.addTensorList(i),[i.idTensor]}case"TensorListConcat":{let r=k("tensorListId",e,t,n),a=n.getTensorList(r.id),s=k("dtype",e,t,n),i=k("elementShape",e,t,n);return[a.concat(s,i)]}case"TensorListPushBack":{let r=k("tensorListId",e,t,n),a=k("tensor",e,t,n),s=n.getTensorList(r.id);return s.pushBack(a),[s.idTensor]}case"TensorListPopBack":{let 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l=vv(s.op);if(l&&l.customExecutor)return l.customExecutor(new ure(s,i,o));throw TypeError(`Custom op ${s.op} is not registered.`);default:throw TypeError(`Unknown op '${s.op}'. 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this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},Wre="?tfjs-format=file",Bre="model.json",Yv=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new Lre}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=bn.browserHTTPRequest(e,this.loadOptions);else{let 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p2(Vv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=Vv.Instance.transformGraph(e.modelInitializer);this.initializer=new p2(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=bn.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 je)&&!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 Tt(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. 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-`).map(e=>(e.endsWith("\r")&&(e=e.slice(0,-1)),e))}},o0='"',Lc=Symbol("out"),h6=Symbol("field"),l0=Symbol("quote"),y2=Symbol("quoteafterquote"),d6=Symbol("quoteinquote"),e6=class extends Ul{constructor(e,t){super();this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new Qv(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((r,a)=>(r[a]=r[a]+1||1,r),{}),n=Object.keys(t).filter(r=>t[r]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let r of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(r)===-1)throw new Error('The key "'+r+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},r={};for(let a=0;a<this.fullColumnNames.length;a++){let s=this.fullColumnNames[a],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[a],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let u=Number(o);if(isNaN(u))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=u;else switch(i.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(o);break;default:l=u}}i&&i.isLabel?r[s]=l:n[s]=l}}return Object.keys(r).length===0?n:{xs:n,ys:r}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],r=0,a=e.length,s=Lc;for(let i=0;i<a;i++)switch(s){case Lc:switch(e.charAt(i)){case o0:r=i+1,s=l0;break;case this.delimiter:if(r=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=Lc;break;default:s=h6,r=i;break}break;case h6:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i)),s=Lc,r=i+1;break;default:}break;case l0:switch(e.charAt(i)){case o0:s=y2;break;default:}break;case y2:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i-1)),s=Lc,r=i+1;break;case o0:s=l0;break;default:s=d6;break}break;case d6:switch(e.charAt(i)){case o0:s=l0;break;default:}break;default:}if(s===y2?n.push(e.substring(r,a-1)):n.push(e.substring(r)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},p6=class extends Zt{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(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new p6(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(a),r({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),xr(n,t)}},f6=class extends Zt{constructor(e,t){super();if(this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=on([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=Nn([s,a,o,i],[1,4])}else this.cropBox=Nn([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new f6(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=al.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return W(()=>{let t=hn(Ae(e,"float32"),0),n;n=Ge.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return G(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},m6=class{},A6=class extends Zt{split(e){return new _ae(this,e)}},_ae=class extends A6{constructor(e,t){super();this.upstream=e,this.impl=new bae(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},bae=class extends A2{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},kae=class extends Zt{decodeUTF8(){return new vae(this)}},vae=class extends A6{constructor(e){super();this.upstream=e,this.impl=new Nae(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Nae=class extends A2{constructor(e){super();if(this.upstream=e,J().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=ck();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return J().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},y6=class extends kae{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(J().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let r=new FileReader;r.onload=s=>{let i=r.result;if(i instanceof 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$ae=[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],Dae=[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],Oae=[33,133,362,263,1,78,308],lhe=$ae.map(e=>w2[e]),uhe=Dae.map(e=>w2[e]),che=Oae.map(e=>w2[e]);var _2=Xr.leftEyeLower0,b2=Xr.rightEyeLower0,ql={leftBounds:[_2[0],_2[_2.length-1]],rightBounds:[b2[0],b2[b2.length-1]]},p0={count:468,mouth:13,symmetryLine:[13,Xr.midwayBetweenEyes[0]]},T6={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Xl={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function f0(e,t,n,r){for(let a=0;a<x2.length;a++){let{key:s,indices:i}=x2[a],o=Xr[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let u=i[l];e[o[l]]=[t[u][0],t[u][1],(t[u][2]+e[o[l]][2])/2]}}}var v2=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Wc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?d0(r,[0,0]):h0,l=r!==0?i.map(h=>[...S6(h,o),h[2]]):i,u=r!==0?I6(a):h0,c=[...Hl({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+Ja(c,u[0]),h[1]+Ja(c,u[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[ql.leftBounds[0]][2],r=t[ql.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=c0(u0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Wc(i),l=Ge.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&Ar.flags.IS_BROWSER&&(l=Ge.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<Xl.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],u=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],u])}return{rawCoords:s,iris:s.slice(Xl.index)}}getAdjustedIrisCoords(t,n,r){let a=t[Xr[`${r}EyeUpper0`][Xl.upperCenter]][2],s=t[Xr[`${r}EyeLower0`][Xl.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let u=i;return l===2?u=a:l===4&&(u=s),[o[0],o[1],u]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=v6({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=u0(o),u=c0(l),c=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...u,confidence:h,landmarks:c}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=W(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,u,c=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&Ar.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=p0.count?p0.symmetryLine:T6.symmetryLine;c=g2(i.landmarks[_],i.landmarks[x]);let I=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),S=[I[0]/t.shape[2],I[1]/t.shape[1]],T=Ge.rotateWithOffset(t,c,0,S);h=d0(-c,I),n.face.mesh.enabled?u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.meshSize,this.meshSize]).div(255):u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.boxSize,this.boxSize]).div(255)}else{h=h0;let _=t.clone();n.face.mesh.enabled?u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:i.confidence,confidence:i.confidence,image:u};let[,d,p]=this.meshDetector.predict(u),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=G(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:_,boxSize:x,crop:I}=this.getEyeBox(A,u,ql.leftBounds[0],ql.leftBounds[1],!0),{box:S,boxSize:T,crop:M}=this.getEyeBox(A,u,ql.rightBounds[0],ql.rightBounds[1]),z=this.irisModel.predict(st([I,M])).dataSync(),B=z.slice(0,Xl.numCoordinates*3),{rawCoords:U,iris:j}=this.getEyeCoords(B,_,x,!0),X=z.slice(Xl.numCoordinates*3),{rawCoords:H,iris:ee}=this.getEyeCoords(X,S,T),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(f0(A,U,"left",null),f0(A,H,"right",null)):Y<1?f0(A,U,"left",["EyeUpper0","EyeLower0"]):f0(A,H,"right",["EyeUpper0","EyeLower0"]);let ae=this.getAdjustedIrisCoords(A,j,"left"),te=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(ae).concat(te)}let y=this.transformRawCoords(A,i,c,h);i=u0(this.calculateLandmarksBoundingBox(y),1.5);let g=Nn(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&n.face.detector.return&&Ar.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=p0.count?p0.symmetryLine:T6.symmetryLine;c=g2(i.landmarks[_],i.landmarks[x]);let I=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),S=[I[0]/t.shape[2],I[1]/t.shape[1]],T=Ge.rotateWithOffset(t,c,0,S);h=d0(-c,I),u=Gl({startPoint:i.startPoint,endPoint:i.endPoint},T,[this.meshSize,this.meshSize]).div(255)}let w={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:u,rawCoords:A},b=c0(i);return this.storedBoxes[o]={...b,landmarks:y,confidence:i.confidence,faceConfidence:f},w}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var Ng=yh(E6());var I2={};Gn(I2,{load:()=>S2,predict:()=>T2});var N2={};function pr(e,t){if(!t||!t.kernels)return;let n=5,r=t.kernels.filter(o=>o.kernelTimeMs>0).reduce((o,l)=>o+=l.kernelTimeMs,0),a=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.kernelTimeMs>0).sort((o,l)=>l.kernelTimeMs-o.kernelTimeMs),s=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.totalBytesSnapshot>0).sort((o,l)=>l.totalBytesSnapshot-o.totalBytesSnapshot);a.length>n&&(a.length=n),s.length>n&&(s.length=n);let i={newBytes:t.newBytes,newTensors:t.newTensors,peakBytes:t.peakBytes,numKernelOps:t.kernels.length,timeKernelOps:r,slowestKernelOps:a,largestKernelOps:s};N2[e]=i,Ee("Human profiler",e,i)}var Qa,m0={age:0},A0=Number.MAX_SAFE_INTEGER;async function S2(e){return Qa||(Qa=await Tt(e.face.age.modelPath),e.debug&&Ee(`load model: ${e.face.age.modelPath.match(/\/(.*)\./)[1]}`)),Qa}async function T2(e,t){return Qa?A0<t.face.age.skipFrames&&t.videoOptimized&&m0.age&&m0.age>0?(A0++,m0):(t.videoOptimized?A0=0:A0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ge.resizeBilinear(e,[Qa.inputs[0].shape[2],Qa.inputs[0].shape[1]],!1),a=P(r,[255]);Te(r);let s,i={age:0};if(!t.profile)t.face.age.enabled&&(s=await Qa.predict(a));else{let o=t.face.age.enabled?await Xn(()=>Qa.predict(a)):{};s=o.result.clone(),o.result.dispose(),pr("age",o)}if(a.dispose(),s){let o=s.dataSync();i.age=Math.trunc(10*o[0])/10}s.dispose(),m0=i,n(i)})):null}var C2={};Gn(C2,{load:()=>M2,predict:()=>$2});var ma,E2={gender:""},y0=Number.MAX_SAFE_INTEGER,R2=!1,F2=[.2989,.587,.114];async function M2(e){return ma||(ma=await Tt(e.face.gender.modelPath),R2=ma.inputs[0].shape[3]===1,e.debug&&Ee(`load model: ${e.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),ma}async function $2(e,t){return ma?y0<t.face.gender.skipFrames&&t.videoOptimized&&E2.gender!==""?(y0++,E2):(t.videoOptimized?y0=0:y0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ge.resizeBilinear(e,[ma.inputs[0].shape[2],ma.inputs[0].shape[1]],!1),a;R2?a=W(()=>{let[o,l,u]=Wt(r,3,3),c=P(o,F2[0]),h=P(l,F2[1]),d=P(u,F2[2]);return $a([c,h,d]).sub(.5).mul(2)}):a=P(r,[255]),Te(r);let s,i={gender:"",confidence:0};if(!t.profile)t.face.gender.enabled&&(s=await ma.predict(a));else{let o=t.face.gender.enabled?await Xn(()=>ma.predict(a)):{};s=o.result.clone(),o.result.dispose(),pr("gender",o)}if(a.dispose(),s){let o=s.dataSync();if(R2)(o[0]>t.face.gender.minConfidence||o[1]>t.face.gender.minConfidence)&&(i.gender=o[0]>o[1]?"female":"male",i.confidence=o[0]>o[1]?Math.trunc(100*o[0])/100:Math.trunc(100*o[1])/100);else{let l=Math.trunc(200*Math.abs(o[0]-.5))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]<=.5?"female":"male",i.confidence=Math.min(.99,l))}}s.dispose(),E2=i,n(i)})):null}var D2={};Gn(D2,{load:()=>P2,predict:()=>L2});var Pae=["angry","disgust","fear","happy","sad","surprise","neutral"],es,O2=[],g0=Number.MAX_SAFE_INTEGER,z2=[.2989,.587,.114];async function 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function W2(e){return Kr||(Kr=await Tt(e.face.embedding.modelPath),e.debug&&Ee(`load model: ${e.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),Kr}function B2(e,t,n=2){if(!e||!t||(e==null?void 0:e.length)===0||(t==null?void 0:t.length)===0||(e==null?void 0:e.length)!==(t==null?void 0:t.length))return 0;let r=e.map((s,i)=>Math.abs(e[i]-t[i])**n).reduce((s,i)=>s+i,0)**(1/n);return Math.max(Math.trunc(1e3*(1-r))/1e3,0)}function R6(e,t,n=0){let r={simmilarity:0,name:"",source:"",embedding:[]};if(!e||!t||!Array.isArray(e)||!Array.isArray(t))return r;for(let a of t)if(a.embedding&&a.name){let s=B2(e,a.embedding);s>n&&s>r.simmilarity&&(r={...a,simmilarity:s})}return r}function V2(e){return W(()=>{let n=[[.05,.15,.85,.85]],r=e.image||e.tensor;if(!(r instanceof je))return null;let a=r.shape.length===3?Ge.cropAndResize(hn(r,0),n,[0],[Kr.inputs[0].shape[2],Kr.inputs[0].shape[1]]):Ge.cropAndResize(r,n,[0],[Kr.inputs[0].shape[2],Kr.inputs[0].shape[1]]),s=[.2989,.587,.114],[i,o,l]=Wt(a,3,3),u=P(i,s[0]),c=P(o,s[1]),h=P(l,s[2]),d=$a([u,c,h]),p=dn([d,d,d],3).squeeze(4),f=p.sub(p.min());return f.div(f.max())})}async function U2(e,t){return Kr?new Promise(async n=>{let r=[];if(t.face.embedding.enabled){let a=V2(e);if(!t.profile)r=W(()=>[...Kr.predict(a).reshape([128,2]).logSumExp(1).dataSync()]);else{let s=await Xn(()=>Kr.predict({img_inputs:a}));r=[...s.result.dataSync()],s.result.dispose(),pr("emotion",s)}Te(a)}n(r)}):[]}var tg={};Gn(tg,{PoseNet:()=>ng,load:()=>rg});function Lae(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var j2=class{constructor(t){this.model=t}predict(t){return W(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=Lae(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function H2(e){return Math.floor(e/2)}var G2=class{constructor(t,n){this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=n}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(H2(t),t);)this.exchange(t,H2(t)),t=H2(t)}sink(t){for(;2*t<=this.numberOfElements;){let 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_=this.transformRawCoords(b,p,l,d),x=this.getBoxForHandLandmarks(_);this.storedBoxes[i]=x;let I={landmarks:_,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(I)}else this.storedBoxes[i]=null;y.dispose()}else{let l=v0(k0(o),e4),u={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(u)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var n4=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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Tt(e.body.modelPath),fr.width=parseInt(fr.signature.inputs["input_1:0"].tensorShape.dim[2].size),fr.height=parseInt(fr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Ee(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),fr}async function fg(e,t){if(!fr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=Ge.resizeBilinear(e,[fr.width,fr.height],!1),a=xe(r,[255]);r.dispose();let s;if(t.profile){let u=await Xn(()=>fr.predict(a));s=u.result.find(c=>c.size===195||c.size===155).dataSync(),u.result.forEach(c=>c.dispose()),pr("blazepose",u)}else{let u=await fr.predict(a);s=u.find(c=>c.size===195||c.size===155).dataSync(),u.forEach(c=>c.dispose())}a.dispose();let i=[],o=s.length===195?r4:a4,l=5;for(let u=0;u<s.length/l;u++)i.push({id:u,part:o[u],position:{x:Math.trunc(n.width*s[l*u+0]/255),y:Math.trunc(n.height*s[l*u+1]/255),z:Math.trunc(s[l*u+2])+0},score:(100-Math.trunc(100/(1+Math.exp(s[l*u+3]))))/100,presence:(100-Math.trunc(100/(1+Math.exp(s[l*u+4]))))/100});return[{keypoints:i}]}var mg={};Gn(mg,{load:()=>yg,predict:()=>gg});var Cr,Ag=[],N0=Number.MAX_SAFE_INTEGER,I0=2.5,lse=["person","bicycle","car","motorcycle","airplane","bus","train","vehicle","boat","traffic light","fire hydrant","stop sign","parking meter","bench","animal","animal","animal","animal","animal","animal","animal","bear","animal","animal","backpack","umbrella","handbag","tie","suitcase","frisbee","skis","snowboard","sports ball","kite","baseball bat","baseball glove","skateboard","surfboard","tennis racket","bottle","wine glass","cup","fork","knife","spoon","bowl","banana","apple","sandwich","orange","broccoli","carrot","hot dog","pizza","pastry","cake","chair","couch","potted plant","bed","dining 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e?e.map(t=>t.id===0&&t.iterationId===0?"":`${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 Yv(e,t,n,r){let a=new Set,s=[],i=null,o=null,l=new Set,c=Object.keys(e).map(d=>Wn(d)[0]),u=[];r!=null&&(u=r.map(d=>Wn(d.name)[0]));let h=[...t];for(;h.length>0;){let d=h.pop();if((Zv(d)||Ire(d)||Nre(d))&&i==null&&(i=d,o=i.children.map(p=>p.name).filter(p=>a.has(p))),a.add(d.name),n[d.name]==null&&c.indexOf(d.name)===-1&&u.indexOf(d.name)===-1){if(d.inputs.length===0){s.push(d.name);continue}d.inputs.forEach(p=>{l.has(p.name)||(l.add(p.name),h.push(p))})}}return{inputs:e,outputs:t,usedNodes:a,missingInputs:s,dynamicNode:i,syncInputs:o}}function Sre(e,t,n){let{usedNodes:r,inputs:a}=n,s=[],i=Object.keys(a).map(u=>Wn(u)[0]).map(u=>e.nodes[u]),o=e.initNodes;i.forEach(u=>{r.has(u.name)&&s.push(u)}),e.weights.forEach(u=>{r.has(u.name)&&s.push(u)}),o!=null&&o.forEach(u=>{r.has(u.name)&&s.push(u)});let l=new Set,c=[];for(;s.length>0;){let u=s.pop();l.add(u.name),t[u.name]||c.push(u),u.children.forEach(h=>{!l.has(h.name)&&r.has(h.name)&&h.inputs.every(d=>l.has(d.name))&&s.push(h)})}return c}var Tre=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],Cre=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],Ere=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function Zv(e){return Tre.indexOf(e.op)>=0}function Ire(e){return Cre.indexOf(e.op)>=0}function Nre(e){return Ere.indexOf(e.op)>=0}var p2=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 p2(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 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RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(let t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);let e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),n}},f2=class extends o6{constructor(){super(f2.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){let e=this.capacity*2,t=new 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uae(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new sae(this,e,t)}columnMajorBatch(e,t=!0,n=s6){return this.rowMajorBatch(e,t).map(r=>Gre(r,n))}concatenate(e,t){return new u6(l6([this,e]),t)}take(e){return e<0||e==null?this:new aae(this,e)}skip(e){return e<0||e==null?this:new rae(this,e)}prefetch(e){return new h6(this,e)}shuffle(e,t){return new cae(this,e,t)}serial(){return new nae(this)}},Yre=class extends Zt{constructor(e){super();this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:Zre(e),done:!1}}},Jre=class extends Zt{constructor(e){super();this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},nae=class extends Zt{constructor(e){super();this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},rae=class extends Zt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;Te(e.value)}return this.upstream.next()}},aae=class extends Zt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},sae=class extends Zt{constructor(e,t,n=!0){super();this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},iae=class extends Zt{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Te(e.value)}}},oae=class extends Zt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=yr.getTensorsInContainer(e.value),n=this.transform(e.value),r=yr.getTensorsInContainer(n);for(let a of t)yr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},lae=class extends Zt{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},c6=class extends Zt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=yr.getTensorsInContainer(e.value),n=await this.transform(e.value),r=yr.getTensorsInContainer(n);for(let a of t)yr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},A2=class extends Zt{constructor(){super();this.outputQueue=new f2,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},uae=class extends A2{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=yr.getTensorsInContainer(e.value),n=this.transform(e.value),r=yr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let a of t)yr.isTensorInList(a,r)||a.dispose();return!0}},u6=class extends Zt{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}},Ya;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(Ya||(Ya={}));var eae=class extends Zt{constructor(e,t=Ya.FAIL){super();this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function r(s){return s instanceof Zt?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await i6(this.iterators,r);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case Ya.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case Ya.SHORTEST:return{value:null,done:!0};case Ya.LONGEST:default:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},h6=class extends Zt{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new o6(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},cae=class extends h6{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=jre.alea(n||v.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},Ul=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
+      ${e}`);let r;return this.size===Infinity||this.size==null?r=this.size:t?r=Math.ceil(this.size/e):r=Math.floor(this.size/e),Bn(async()=>(await n.iterator()).columnMajorBatch(e,t,hae),r)}concatenate(e){let t=this,n;return this.size===Infinity||e.size===Infinity?n=Infinity:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Bn(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===Infinity?n=Infinity:n=null,Bn(async()=>(await t.iterator()).filter(r=>L(()=>e(r))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Bn(async()=>(await t.iterator()).map(n=>L(()=>e(n))),this.size)}mapAsync(e){let t=this;return Bn(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Bn(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=Infinity:n=null,Bn(async()=>{let r=m2(async()=>({value:await t.iterator(),done:!1}));return Qre(r.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Bn(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let r=this,a=Ure.alea(t||v.now().toString());return Bn(async()=>{let s=a.int32();return n&&(s+=a.int32()),(await r.iterator()).shuffle(e,s.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Bn(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Ul.MAX_BUFFER_SIZE=1e4;function Bn(e,t=null){return new class extends Ul{constructor(){super(...arguments);this.size=t}async iterator(){return e()}}}function Dre(e){return Bn(async()=>l6(e),e.length)}function Ore(e){if(!jl(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Bn(async()=>{let n=await i6(e,r=>{if(r instanceof Ul)return{value:r.iterator(),recurse:!1};if(jl(r))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return tae(n,Ya.SHORTEST)},t)}function hae(e){if(e===null)return null;let t=e[0];return Xre(t)?{value:dae(e),recurse:!1}:{value:null,recurse:!0}}function dae(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof je?dn(e):xr(e)}var e6=class extends Ul{constructor(e){super();this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
+`).map(e=>(e.endsWith("\r")&&(e=e.slice(0,-1)),e))}},l0='"',Wc=Symbol("out"),d6=Symbol("field"),u0=Symbol("quote"),y2=Symbol("quoteafterquote"),p6=Symbol("quoteinquote"),t6=class extends Ul{constructor(e,t){super();this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new e6(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((r,a)=>(r[a]=r[a]+1||1,r),{}),n=Object.keys(t).filter(r=>t[r]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let r of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(r)===-1)throw new Error('The key "'+r+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},r={};for(let a=0;a<this.fullColumnNames.length;a++){let s=this.fullColumnNames[a],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[a],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let c=Number(o);if(isNaN(c))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=c;else switch(i.dtype){case"float32":l=c;break;case"int32":l=Math.floor(c);break;case"bool":l=this.getBoolean(o);break;default:l=c}}i&&i.isLabel?r[s]=l:n[s]=l}}return Object.keys(r).length===0?n:{xs:n,ys:r}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],r=0,a=e.length,s=Wc;for(let i=0;i<a;i++)switch(s){case Wc:switch(e.charAt(i)){case l0:r=i+1,s=u0;break;case this.delimiter:if(r=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=Wc;break;default:s=d6,r=i;break}break;case d6:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i)),s=Wc,r=i+1;break;default:}break;case u0:switch(e.charAt(i)){case l0:s=y2;break;default:}break;case y2:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(r,i-1)),s=Wc,r=i+1;break;case l0:s=u0;break;default:s=p6;break}break;case p6:switch(e.charAt(i)){case l0:s=u0;break;default:}break;default:}if(s===y2?n.push(e.substring(r,a-1)):n.push(e.substring(r)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},f6=class extends Zt{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(J().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new f6(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(a),r({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),xr(n,t)}},m6=class extends Zt{constructor(e,t){super();if(this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=on([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=In([s,a,o,i],[1,4])}else this.cropBox=In([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(J().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new m6(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=al.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: 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Nae=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],Sae=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],Tae=[33,133,362,263,1,78,308],ehe=Nae.map(e=>w2[e]),the=Sae.map(e=>w2[e]),nhe=Tae.map(e=>w2[e]);var b2=Xr.leftEyeLower0,_2=Xr.rightEyeLower0,ql={leftBounds:[b2[0],b2[b2.length-1]],rightBounds:[_2[0],_2[_2.length-1]]},f0={count:468,mouth:13,symmetryLine:[13,Xr.midwayBetweenEyes[0]]},C6={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Xl={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function m0(e,t,n,r){for(let a=0;a<x2.length;a++){let{key:s,indices:i}=x2[a],o=Xr[`${n}${s}`];if(!r||r.includes(s))for(let l=0;l<i.length;l++){let c=i[l];e[o[l]]=[t[c][0],t[c][1],(t[c][2]+e[o[l]][2])/2]}}}var v2=class{constructor(t,n,r){var a,s;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=r,this.boxSize=((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((s=t==null?void 0:t.model)==null?void 0:s.inputs[0].shape[2]),this.irisSize=(r==null?void 0:r.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,r,a){let s=Bc({startPoint:n.startPoint,endPoint:n.endPoint}),i=t.map(h=>[s[0]/this.meshSize*(h[0]-this.meshSize/2),s[1]/this.meshSize*(h[1]-this.meshSize/2),h[2]]),o=r!==0?p0(r,[0,0]):d0,l=r!==0?i.map(h=>[...T6(h,o),h[2]]):i,c=r!==0?S6(a):d0,u=[...Hl({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(h=>[h[0]+Ja(u,c[0]),h[1]+Ja(u,c[1]),h[2]])}getLeftToRightEyeDepthDifference(t){let n=t[ql.leftBounds[0]][2],r=t[ql.rightBounds[0]][2];return n-r}getEyeBox(t,n,r,a,s=!1){let i=h0(c0(this.calculateLandmarksBoundingBox([t[r],t[a]]),this.irisEnlarge)),o=Bc(i),l=Ge.cropAndResize(n,[[i.startPoint[1]/this.meshSize,i.startPoint[0]/this.meshSize,i.endPoint[1]/this.meshSize,i.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return s&&Ar.flags.IS_BROWSER&&(l=Ge.flipLeftRight(l)),{box:i,boxSize:o,crop:l}}getEyeCoords(t,n,r,a=!1){let s=[];for(let i=0;i<Xl.numCoordinates;i++){let o=t[i*3],l=t[i*3+1],c=t[i*3+2];s.push([(a?1-o/this.irisSize:o/this.irisSize)*r[0]+n.startPoint[0],l/this.irisSize*r[1]+n.startPoint[1],c])}return{rawCoords:s,iris:s.slice(Xl.index)}}getAdjustedIrisCoords(t,n,r){let a=t[Xr[`${r}EyeUpper0`][Xl.upperCenter]][2],s=t[Xr[`${r}EyeLower0`][Xl.lowerCenter]][2],i=(a+s)/2;return n.map((o,l)=>{let c=i;return l===2?c=a:l===4&&(c=s),[o[0],o[1],c]})}async predict(t,n){let r=!1,a;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.videoOptimized)&&(a=await this.boundingBoxDetector.getBoundingBoxes(t),this.skipped=0),n.videoOptimized&&this.skipped++,a&&a.boxes&&(!n.face.mesh.enabled||a.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let i of a.boxes)this.storedBoxes.push({startPoint:i.box.startPoint.dataSync(),endPoint:i.box.endPoint.dataSync(),landmarks:i.landmarks,confidence:i.confidence});this.storedBoxes.length>0&&(r=!0)}if(n.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),r){if(!a||!a.boxes||a.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let i=0;i<this.storedBoxes.length;i++){let o=k6({startPoint:this.storedBoxes[i].startPoint,endPoint:this.storedBoxes[i].endPoint},a.scaleFactor),l=c0(o),c=h0(l),u=this.storedBoxes[i].landmarks.arraySync(),h=this.storedBoxes[i].confidence;this.storedBoxes[i]={...c,confidence:h,landmarks:u}}}a&&a.boxes&&a.boxes.forEach(i=>{i.box.startPoint.dispose(),i.box.endPoint.dispose(),i.landmarks.dispose()});let s=L(()=>this.storedBoxes.map((i,o)=>{let l=i.confidence,c,u=0,h;if(n.face.detector.rotation&&n.face.mesh.enabled&&Ar.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=f0.count?f0.symmetryLine:C6.symmetryLine;u=g2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],C=Ge.rotateWithOffset(t,u,0,T);h=p0(-u,N),n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},C,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},C,[this.boxSize,this.boxSize]).div(255)}else{h=d0;let _=t.clone();n.face.mesh.enabled?c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.meshSize,this.meshSize]).div(255):c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},_,[this.boxSize,this.boxSize]).div(255)}if(!n.face.mesh.enabled)return{coords:null,box:i,faceConfidence:null,boxConfidence:i.confidence,confidence:i.confidence,image:c};let[,d,p]=this.meshDetector.predict(c),f=d.dataSync()[0];if(f<n.face.detector.minConfidence)return null;let A=H(p,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:_,boxSize:x,crop:N}=this.getEyeBox(A,c,ql.leftBounds[0],ql.leftBounds[1],!0),{box:T,boxSize:C,crop:F}=this.getEyeBox(A,c,ql.rightBounds[0],ql.rightBounds[1]),B=this.irisModel.predict(at([N,F])).dataSync(),V=B.slice(0,Xl.numCoordinates*3),{rawCoords:U,iris:j}=this.getEyeCoords(V,_,x,!0),X=B.slice(Xl.numCoordinates*3),{rawCoords:G,iris:ee}=this.getEyeCoords(X,T,C),Y=this.getLeftToRightEyeDepthDifference(A);Math.abs(Y)<30?(m0(A,U,"left",null),m0(A,G,"right",null)):Y<1?m0(A,U,"left",["EyeUpper0","EyeLower0"]):m0(A,G,"right",["EyeUpper0","EyeLower0"]);let ae=this.getAdjustedIrisCoords(A,j,"left"),te=this.getAdjustedIrisCoords(A,ee,"right");A=A.concat(ae).concat(te)}let y=this.transformRawCoords(A,i,u,h);i=c0(this.calculateLandmarksBoundingBox(y),1.5);let g=In(y);if(n.face.detector.rotation&&n.face.mesh.enabled&&n.face.detector.return&&Ar.flags.IS_BROWSER){let[_,x]=i.landmarks.length>=f0.count?f0.symmetryLine:C6.symmetryLine;u=g2(i.landmarks[_],i.landmarks[x]);let N=Hl({startPoint:i.startPoint,endPoint:i.endPoint}),T=[N[0]/t.shape[2],N[1]/t.shape[1]],C=Ge.rotateWithOffset(t,u,0,T);h=p0(-u,N),c=Gl({startPoint:i.startPoint,endPoint:i.endPoint},C,[this.meshSize,this.meshSize]).div(255)}let w={coords:g,box:i,faceConfidence:f,boxConfidence:l,image:c,rawCoords:A},b=h0(i);return this.storedBoxes[o]={...b,landmarks:y,confidence:i.confidence,faceConfidence:f},w}));return s=s.filter(i=>i!==null),n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(i=>i.faceConfidence>n.face.detector.minConfidence)),this.detectedFaces=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s,landmarks:t}}};var kg=gh(R6());var N2={};Gn(N2,{load:()=>S2,predict:()=>T2});var I2={};function pr(e,t){if(!t||!t.kernels)return;let n=5,r=t.kernels.filter(o=>o.kernelTimeMs>0).reduce((o,l)=>o+=l.kernelTimeMs,0),a=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.kernelTimeMs>0).sort((o,l)=>l.kernelTimeMs-o.kernelTimeMs),s=t.kernels.map((o,l)=>(o.id=l,o)).filter(o=>o.totalBytesSnapshot>0).sort((o,l)=>l.totalBytesSnapshot-o.totalBytesSnapshot);a.length>n&&(a.length=n),s.length>n&&(s.length=n);let i={newBytes:t.newBytes,newTensors:t.newTensors,peakBytes:t.peakBytes,numKernelOps:t.kernels.length,timeKernelOps:r,slowestKernelOps:a,largestKernelOps:s};I2[e]=i,Ee("Human profiler",e,i)}var Qa,A0={age:0},y0=Number.MAX_SAFE_INTEGER;async function S2(e){return Qa||(Qa=await Tt(e.face.age.modelPath),e.debug&&Ee(`load model: ${e.face.age.modelPath.match(/\/(.*)\./)[1]}`)),Qa}async function T2(e,t){return Qa?y0<t.face.age.skipFrames&&t.videoOptimized&&A0.age&&A0.age>0?(y0++,A0):(t.videoOptimized?y0=0:y0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ge.resizeBilinear(e,[Qa.inputs[0].shape[2],Qa.inputs[0].shape[1]],!1),a=O(r,[255]);Te(r);let s,i={age:0};if(!t.profile)t.face.age.enabled&&(s=await Qa.predict(a));else{let o=t.face.age.enabled?await Xn(()=>Qa.predict(a)):{};s=o.result.clone(),o.result.dispose(),pr("age",o)}if(a.dispose(),s){let o=s.dataSync();i.age=Math.trunc(10*o[0])/10}s.dispose(),A0=i,n(i)})):null}var C2={};Gn(C2,{load:()=>F2,predict:()=>$2});var ma,E2={gender:""},g0=Number.MAX_SAFE_INTEGER,R2=!1,M2=[.2989,.587,.114];async function F2(e){return ma||(ma=await Tt(e.face.gender.modelPath),R2=ma.inputs[0].shape[3]===1,e.debug&&Ee(`load model: ${e.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),ma}async function $2(e,t){return ma?g0<t.face.gender.skipFrames&&t.videoOptimized&&E2.gender!==""?(g0++,E2):(t.videoOptimized?g0=0:g0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ge.resizeBilinear(e,[ma.inputs[0].shape[2],ma.inputs[0].shape[1]],!1),a;R2?a=L(()=>{let[o,l,c]=Wt(r,3,3),u=O(o,M2[0]),h=O(l,M2[1]),d=O(c,M2[2]);return $a([u,h,d]).sub(.5).mul(2)}):a=O(r,[255]),Te(r);let s,i={gender:"",confidence:0};if(!t.profile)t.face.gender.enabled&&(s=await ma.predict(a));else{let o=t.face.gender.enabled?await Xn(()=>ma.predict(a)):{};s=o.result.clone(),o.result.dispose(),pr("gender",o)}if(a.dispose(),s){let o=s.dataSync();if(R2)(o[0]>t.face.gender.minConfidence||o[1]>t.face.gender.minConfidence)&&(i.gender=o[0]>o[1]?"female":"male",i.confidence=o[0]>o[1]?Math.trunc(100*o[0])/100:Math.trunc(100*o[1])/100);else{let l=Math.trunc(200*Math.abs(o[0]-.5))/100;l>t.face.gender.minConfidence&&(i.gender=o[0]<=.5?"female":"male",i.confidence=Math.min(.99,l))}}s.dispose(),E2=i,n(i)})):null}var D2={};Gn(D2,{load:()=>P2,predict:()=>L2});var Eae=["angry","disgust","fear","happy","sad","surprise","neutral"],es,O2=[],x0=Number.MAX_SAFE_INTEGER,z2=[.2989,.587,.114];async function P2(e){return es||(es=await Tt(e.face.emotion.modelPath),e.debug&&Ee(`load model: ${e.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),es}async function L2(e,t){return es?x0<t.face.emotion.skipFrames&&t.videoOptimized&&O2.length>0?(x0++,O2):(t.videoOptimized?x0=0:x0=Number.MAX_SAFE_INTEGER,new Promise(async n=>{let r=Ge.resizeBilinear(e,[es.inputs[0].shape[2],es.inputs[0].shape[1]],!1),[a,s,i]=Wt(r,3,3);r.dispose();let o=O(a,z2[0]),l=O(s,z2[1]),c=O(i,z2[2]);a.dispose(),s.dispose(),i.dispose();let u=$a([o,l,c]);o.dispose(),l.dispose(),c.dispose();let h=L(()=>u.sub(.5).mul(2));u.dispose();let d=[];if(t.face.emotion.enabled){let p;if(t.profile){let f=await Xn(()=>es.predict(h));p=f.result.dataSync(),f.result.dispose(),pr("emotion",f)}else{let f=await es.predict(h);p=f.dataSync(),Te(f)}for(let f=0;f<p.length;f++)p[f]>t.face.emotion.minConfidence&&d.push({score:Math.min(.99,Math.trunc(100*p[f])/100),emotion:Eae[f]});d.sort((f,m)=>m.score-f.score)}h.dispose(),O2=d,n(d)})):null}var Kr;async function W2(e){return Kr||(Kr=await Tt(e.face.embedding.modelPath),e.debug&&Ee(`load model: ${e.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),Kr}function B2(e,t,n=2){if(!e||!t||(e==null?void 0:e.length)===0||(t==null?void 0:t.length)===0||(e==null?void 0:e.length)!==(t==null?void 0:t.length))return 0;let r=e.map((s,i)=>Math.abs(e[i]-t[i])**n).reduce((s,i)=>s+i,0)**(1/n);return Math.max(Math.trunc(1e3*(1-r))/1e3,0)}function M6(e,t,n=0){let r={simmilarity:0,name:"",source:"",embedding:[]};if(!e||!t||!Array.isArray(e)||!Array.isArray(t))return r;for(let a of t)if(a.embedding&&a.name){let s=B2(e,a.embedding);s>n&&s>r.simmilarity&&(r={...a,simmilarity:s})}return r}function V2(e){return L(()=>{let n=[[.05,.15,.85,.85]],r=e.image||e.tensor;if(!(r instanceof je))return null;let a=r.shape.length===3?Ge.cropAndResize(hn(r,0),n,[0],[Kr.inputs[0].shape[2],Kr.inputs[0].shape[1]]):Ge.cropAndResize(r,n,[0],[Kr.inputs[0].shape[2],Kr.inputs[0].shape[1]]),s=[.2989,.587,.114],[i,o,l]=Wt(a,3,3),c=O(i,s[0]),u=O(o,s[1]),h=O(l,s[2]),d=$a([c,u,h]),p=dn([d,d,d],3).squeeze(4),f=p.sub(p.min());return f.div(f.max())})}async function U2(e,t){return Kr?new Promise(async n=>{let r=[];if(t.face.embedding.enabled){let a=V2(e);if(!t.profile)r=L(()=>[...Kr.predict(a).reshape([128,2]).logSumExp(1).dataSync()]);else{let s=await Xn(()=>Kr.predict({img_inputs:a}));r=[...s.result.dataSync()],s.result.dispose(),pr("emotion",s)}Te(a)}n(r)}):[]}var tg={};Gn(tg,{PoseNet:()=>ng,load:()=>rg});function Rae(e){let[t,n,r,a]=e;return{offsets:t,heatmap:n,displacementFwd:r,displacementBwd:a}}var j2=class{constructor(t){this.model=t}predict(t){return L(()=>{let r=t.toFloat().div(127.5).sub(1).expandDims(0),s=this.model.predict(r).map(o=>o.squeeze([0])),i=Rae(s);return{heatmapScores:i.heatmap.sigmoid(),offsets:i.offsets,displacementFwd:i.displacementFwd,displacementBwd:i.displacementBwd}})}dispose(){this.model.dispose()}};function H2(e){return Math.floor(e/2)}var G2=class{constructor(t,n){this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=n}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(H2(t),t);)this.exchange(t,H2(t)),t=H2(t)}sink(t){for(;2*t<=this.numberOfElements;){let 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_=this.transformRawCoords(b,p,l,d),x=this.getBoxForHandLandmarks(_);this.storedBoxes[i]=x;let N={landmarks:_,confidence:g,box:{topLeft:x.startPoint,bottomRight:x.endPoint}};s.push(N)}else this.storedBoxes[i]=null;y.dispose()}else{let l=k0(I0(o),t4),c={confidence:o.confidence,box:{topLeft:l.startPoint,bottomRight:l.endPoint}};s.push(c)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=s.length,s}calculateLandmarksBoundingBox(t){let n=t.map(i=>i[0]),r=t.map(i=>i[1]),a=[Math.min(...n),Math.min(...r)],s=[Math.max(...n),Math.max(...r)];return{startPoint:a,endPoint:s}}};var r4=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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a4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],s4=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var fr;async function pg(e){return fr||(fr=await Tt(e.body.modelPath),fr.width=parseInt(fr.signature.inputs["input_1:0"].tensorShape.dim[2].size),fr.height=parseInt(fr.signature.inputs["input_1:0"].tensorShape.dim[1].size),e.debug&&Ee(`load model: ${e.body.modelPath.match(/\/(.*)\./)[1]}`)),fr}async function fg(e,t){if(!fr||!t.body.enabled)return null;let n={width:e.shape[2],height:e.shape[1]},r=Ge.resizeBilinear(e,[fr.width,fr.height],!1),a=xe(r,[255]);r.dispose();let s;if(t.profile){let c=await Xn(()=>fr.predict(a));s=c.result.find(u=>u.size===195||u.size===155).dataSync(),c.result.forEach(u=>u.dispose()),pr("blazepose",c)}else{let c=await fr.predict(a);s=c.find(u=>u.size===195||u.size===155).dataSync(),c.forEach(u=>u.dispose())}a.dispose();let i=[],o=s.length===195?a4:s4,l=5;for(let 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a,s=[];s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),s.length===5&&kg(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftKnee"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftAnkle"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHeel"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftFoot"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),R0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightKnee"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightAnkle"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHeel"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightFoot"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),R0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftElbow"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftWrist"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftPalm"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),R0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightElbow"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightWrist"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightPalm"),a&&a.score>mt.body.scoreThreshold&&s.push([a.position.x,a.position.y]),R0(n,s)}}}}async function C4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=oe.font;for(let r of t){if(oe.drawBoxes&&(n.strokeStyle=oe.color,n.fillStyle=oe.color,vg(n,r.box[0],r.box[1],r.box[2],r.box[3]),oe.drawLabels&&(oe.shadowColor&&oe.shadowColor!==""&&(n.fillStyle=oe.shadowColor,n.fillText("hand",r.box[0]+3,1+r.box[1]+oe.lineHeight,r.box[2])),n.fillStyle=oe.labelColor,n.fillText("hand",r.box[0]+2,0+r.box[1]+oe.lineHeight,r.box[2])),n.stroke()),oe.drawPoints&&r.landmarks&&r.landmarks.length>0)for(let a of r.landmarks)n.fillStyle=oe.useDepth?`rgba(${127.5+2*a[2]}, ${127.5-2*a[2]}, 255, 0.5)`:oe.color,E0(n,a[0],a[1]);if(oe.drawPolygons){let a=s=>{if(!!s)for(let i=0;i<s.length;i++)n.lineWidth=oe.lineWidth,n.beginPath(),n.strokeStyle=oe.useDepth?`rgba(${127.5+2*s[i][2]}, ${127.5-2*s[i][2]}, 255, 0.5)`:oe.color,n.moveTo(s[i>0?i-1:0][0],s[i>0?i-1:0][1]),n.lineTo(s[i][0],s[i][1]),n.stroke()};a(r.annotations.indexFinger),a(r.annotations.middleFinger),a(r.annotations.ringFinger),a(r.annotations.pinky),a(r.annotations.thumb)}}}}async function E4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=oe.font;for(let r of t)if(oe.drawBoxes){if(n.strokeStyle=oe.color,n.fillStyle=oe.color,vg(n,r.box[0],r.box[1],r.box[2]-r.box[0],r.box[3]-r.box[1]),oe.drawLabels){let a=`${Math.round(100*r.score)}% ${r.label}`;oe.shadowColor&&oe.shadowColor!==""&&(n.fillStyle=oe.shadowColor,n.fillText(a,r.box[0]+3,1+r.box[1]+oe.lineHeight,r.box[2])),n.fillStyle=oe.labelColor,n.fillText(a,r.box[0]+2,0+r.box[1]+oe.lineHeight,r.box[2])}n.stroke()}}}async function dse(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function pse(e,t){!t||!e||e instanceof HTMLCanvasElement&&(S4(e,t.face),T4(e,t.body),C4(e,t.hand),I4(e,t.gesture),E4(e,t.object))}var ot=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Vc(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,r)=>(Object.keys(r||{}).forEach(a=>{let s=n[a],i=r[a];Array.isArray(s)&&Array.isArray(i)?n[a]=s.concat(...i):t(s)&&t(i)?n[a]=Vc(s,i):n[a]=i}),n),{})}var F0,Ve,Kl,Uc,jc,Di,Rt,M0,Hc,$0,Gc,D0,O0,z0,Ig=class{constructor(t={}){F0.set(this,void 0);Ve.set(this,void 0);Kl.set(this,void 0);Uc.set(this,void 0);jc.set(this,void 0);Di.set(this,void 0);Rt.set(this,(...t)=>{if(!me(this,Uc))return;let n=this.tf.engine().state.numTensors,r=me(this,Kl);ta(this,Kl,n);let a=n-r;a!==0&&Ee(...t,a)});M0.set(this,t=>{if(!me(this,jc))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof je))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Hc.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=ot();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.config.debug&&Ee("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Ee("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Ee(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Ee("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&x6();try{await this.tf.setBackend(this.config.backend)}catch(r){Ee("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(Ee("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Ee(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),me(this,Ve).backend=Math.trunc(ot()-n)}});$0.set(this,t=>{if(!t||t.length<300)return{roll:null,yaw:null,pitch:null};let n=(s,i,o,l)=>Math.atan2(l-i,o-s),r=s=>Math.abs(s*180/Math.PI%360);return{roll:n(t[33][0],t[33][1],t[263][0],t[263][1]),yaw:n(t[33][0],t[33][2],t[263][0],t[263][2]),pitch:n(t[10][1],t[10][2],t[152][1],t[152][2])}});Gc.set(this,async t=>{var u,c,h,d,p,f,m;let n,r,a,s,i,o=[];this.state="run:face",n=ot();let l=await((u=this.models.face)==null?void 0:u.estimateFaces(t,this.config));if(me(this,Ve).face=Math.trunc(ot()-n),!l)return[];for(let A of l){if(me(this,Rt).call(this,"Get Face"),!A.image||A.image.isDisposedInternal){Ee("Face object is disposed:",A.image);continue}let y=me(this,$0).call(this,A.mesh);me(this,Rt).call(this,"Start Age:"),this.config.async?r=this.config.face.age.enabled?T2(A.image,this.config):{}:(this.state="run:age",n=ot(),r=this.config.face.age.enabled?await T2(A.image,this.config):{},me(this,Ve).age=Math.trunc(ot()-n)),me(this,Rt).call(this,"Start Gender:"),this.config.async?a=this.config.face.gender.enabled?$2(A.image,this.config):{}:(this.state="run:gender",n=ot(),a=this.config.face.gender.enabled?await $2(A.image,this.config):{},me(this,Ve).gender=Math.trunc(ot()-n)),me(this,Rt).call(this,"Start Emotion:"),this.config.async?s=this.config.face.emotion.enabled?L2(A.image,this.config):{}:(this.state="run:emotion",n=ot(),s=this.config.face.emotion.enabled?await L2(A.image,this.config):{},me(this,Ve).emotion=Math.trunc(ot()-n)),me(this,Rt).call(this,"End Emotion:"),me(this,Rt).call(this,"Start Embedding:"),this.config.async?i=this.config.face.embedding.enabled?U2(A,this.config):[]:(this.state="run:embedding",n=ot(),i=this.config.face.embedding.enabled?await U2(A,this.config):[],me(this,Ve).embedding=Math.trunc(ot()-n)),me(this,Rt).call(this,"End Emotion:"),this.config.async&&([r,a,s,i]=await Promise.all([r,a,s,i])),me(this,Rt).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((c=A==null?void 0:A.annotations)==null?void 0:c.leftEyeIris)&&((h=A==null?void 0:A.annotations)==null?void 0:h.rightEyeIris)&&(delete A.annotations.leftEyeIris,delete A.annotations.rightEyeIris);let g=((d=A.annotations)==null?void 0:d.leftEyeIris)&&((p=A.annotations)==null?void 0:p.rightEyeIris)?11.7*Math.max(Math.abs(A.annotations.leftEyeIris[3][0]-A.annotations.leftEyeIris[1][0]),Math.abs(A.annotations.rightEyeIris[4][1]-A.annotations.rightEyeIris[2][1])):0;o.push({...A,age:r.age,gender:a.gender,genderConfidence:a.confidence,emotion:s,embedding:i,iris:g!==0?Math.trunc(g)/100:0,angle:y,tensor:this.config.face.detector.return?(f=A.image)==null?void 0:f.squeeze():null}),(m=A.image)==null||m.dispose(),me(this,Rt).call(this,"End Face")}return me(this,Rt).call(this,"End FaceMesh:"),this.config.async&&(me(this,Ve).face&&delete me(this,Ve).face,me(this,Ve).age&&delete me(this,Ve).age,me(this,Ve).gender&&delete me(this,Ve).gender,me(this,Ve).emotion&&delete me(this,Ve).emotion),o});D0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(T0);break;case"full":n=await t(C0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});O0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+T0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+C0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));z0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(T0):t(C0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=gh,this.draw=bg,ta(this,F0,wg),this.version=_g,this.config=Vc(mt,t),this.state="idle",ta(this,Kl,0),ta(this,Uc,!1),ta(this,jc,!1),ta(this,Di,!0),ta(this,Ve,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=n=>xg(n,this.config),this.classes={facemesh:Ng,age:I2,gender:C2,emotion:D2,body:this.config.body.modelPath.includes("posenet")?tg:dg,hand:lg,nanodet:mg},this.sysinfo=Bg()}profileData(){return this.config.profile?N2:{}}simmilarity(t,n){return this.config.face.embedding.enabled?B2(t,n):0}enhance(t){return V2(t)}match(t,n,r=0){return R6(t,n,r)}async load(t={}){this.state="load";let n=ot();t&&(this.config=Vc(this.config,t)),me(this,Di)&&(this.config.debug&&Ee(`version: ${this.version}`),this.config.debug&&Ee(`tfjs version: ${this.tf.version_core}`),this.config.debug&&Ee("platform:",this.sysinfo.platform),this.config.debug&&Ee("agent:",this.sysinfo.agent),await me(this,Hc).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&Ee("configuration:",this.config),this.config.debug&&Ee("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?Ng.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?S2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?M2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?P2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?W2(this.config):null),this.models.handpose||(this.config.hand.enabled?hg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?rg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?pg(this.config):null),this.models.nanodet||(this.config.object.enabled?yg(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await Ng.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await S2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await M2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await P2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await W2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await hg(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await rg(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await pg(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await yg(this.config))),me(this,Di)&&(this.config.debug&&Ee("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),ta(this,Di,!1));let r=Math.trunc(ot()-n);r>(me(this,Ve).load||0)&&(me(this,Ve).load=r)}async detect(t,n={}){return new Promise(async r=>{var p,f,m,A;this.state="config";let a;this.config=Vc(this.config,n),this.state="check";let s=me(this,M0).call(this,t);s&&(Ee(s,t),r({error:s}));let i=ot();await me(this,Hc).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),me(this,Rt).call(this,"Start Scope:"),a=ot();let o=xg(t,this.config);if(!o||!o.tensor){Ee("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}me(this,Ve).image=Math.trunc(ot()-a),me(this,Rt).call(this,"Get Image:");let l,u,c,h;this.config.async?(c=this.config.face.enabled?me(this,Gc).call(this,o.tensor):[],me(this,Ve).face&&delete me(this,Ve).face):(this.state="run:face",a=ot(),c=this.config.face.enabled?await me(this,Gc).call(this,o.tensor):[],me(this,Ve).face=Math.trunc(ot()-a)),me(this,Rt).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(p=this.models.posenet)==null?void 0:p.estimatePoses(o.tensor,this.config):[]:l=this.config.body.enabled?fg(o.tensor,this.config):[],me(this,Ve).body&&delete me(this,Ve).body):(this.state="run:body",a=ot(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((f=this.models.posenet)==null?void 0:f.estimatePoses(o.tensor,this.config)):[]:l=this.config.body.enabled?await fg(o.tensor,this.config):[],me(this,Ve).body=Math.trunc(ot()-a)),me(this,Rt).call(this,"End Body:"),me(this,Rt).call(this,"Start Hand:"),this.config.async?(u=this.config.hand.enabled?(m=this.models.handpose)==null?void 0:m.estimateHands(o.tensor,this.config):[],me(this,Ve).hand&&delete me(this,Ve).hand):(this.state="run:hand",a=ot(),u=this.config.hand.enabled?await((A=this.models.handpose)==null?void 0:A.estimateHands(o.tensor,this.config)):[],me(this,Ve).hand=Math.trunc(ot()-a)),me(this,Rt).call(this,"End Hand:"),me(this,Rt).call(this,"Start Object:"),this.config.async?(h=this.config.object.enabled?gg(o.tensor,this.config):[],me(this,Ve).object&&delete me(this,Ve).object):(this.state="run:object",a=ot(),h=this.config.object.enabled?await gg(o.tensor,this.config):[],me(this,Ve).object=Math.trunc(ot()-a)),me(this,Rt).call(this,"End Object:"),this.config.async&&([c,l,u,h]=await Promise.all([c,l,u,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),me(this,Rt).call(this,"End Scope:");let d=[];this.config.gesture.enabled&&(a=ot(),d=[...i4(c),...s4(l),...l4(u),...o4(c)],this.config.async?me(this,Ve).gesture&&delete me(this,Ve).gesture:me(this,Ve).gesture=Math.trunc(ot()-a)),me(this,Ve).total=Math.trunc(ot()-i),this.state="idle",r({face:c,body:l,hand:u,gesture:d,object:h,performance:me(this,Ve),canvas:o.canvas})})}async warmup(t={}){let n=ot();t&&(this.config=Vc(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await me(this,D0).call(this):typeof Image!="undefined"?a=await me(this,O0).call(this):a=await me(this,z0).call(this),this.config.videoOptimized=r;let s=ot();return this.config.debug&&Ee("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};F0=new WeakMap,Ve=new WeakMap,Kl=new WeakMap,Uc=new WeakMap,jc=new WeakMap,Di=new WeakMap,Rt=new WeakMap,M0=new WeakMap,Hc=new WeakMap,$0=new WeakMap,Gc=new WeakMap,D0=new WeakMap,O0=new WeakMap,z0=new WeakMap;return fse;})();
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t){n.font=ie.font,n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.drawBoxes&&(ie.useRawBoxes?Kl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Kl(n,r.box[0],r.box[1],r.box[2],r.box[3]));let a=[];if(a.push(`face confidence: ${Math.trunc(100*r.confidence)}%`),r.genderConfidence&&a.push(`${r.gender||""} ${Math.trunc(100*r.genderConfidence)}% confident`),r.age&&a.push(`age: ${r.age||""}`),r.iris&&a.push(`iris distance: ${r.iris}`),r.emotion&&r.emotion.length>0){let s=r.emotion.map(i=>`${Math.trunc(100*i.score)}% ${i.emotion}`);a.push(s.join(" "))}r.angle&&r.angle.roll&&a.push(`roll: ${Math.trunc(100*r.angle.roll)/100} yaw:${Math.trunc(100*r.angle.yaw)/100} pitch:${Math.trunc(100*r.angle.pitch)/100}`),a.length===0&&a.push("face"),n.fillStyle=ie.color;for(let s=a.length-1;s>=0;s--){let i=Math.max(r.box[0],0),o=s*ie.lineHeight+r.box[1];ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText(a[s],i+5,o+16)),n.fillStyle=ie.labelColor,n.fillText(a[s],i+4,o+15)}if(n.lineWidth=1,r.mesh&&r.mesh.length>0){if(ie.drawPoints)for(let s of r.mesh)R0(n,s[0],s[1],s[2]);if(ie.drawPolygons){n.lineWidth=1;for(let s=0;s<Fi.length/3;s++){let i=[Fi[s*3+0],Fi[s*3+1],Fi[s*3+2]].map(o=>r.mesh[o]);vg(n,i)}if(r.annotations&&r.annotations.leftEyeIris){n.strokeStyle=ie.useDepth?"rgba(255, 200, 255, 0.3)":ie.color,n.beginPath();let s=Math.abs(r.annotations.leftEyeIris[3][0]-r.annotations.leftEyeIris[1][0])/2,i=Math.abs(r.annotations.leftEyeIris[4][1]-r.annotations.leftEyeIris[2][1])/2;n.ellipse(r.annotations.leftEyeIris[0][0],r.annotations.leftEyeIris[0][1],s,i,0,0,2*Math.PI),n.stroke(),ie.fillPolygons&&(n.fillStyle=ie.useDepth?"rgba(255, 255, 200, 0.3)":ie.color,n.fill())}if(r.annotations&&r.annotations.rightEyeIris){n.strokeStyle=ie.useDepth?"rgba(255, 200, 255, 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0.5)`:ie.color,ie.bufferedOutput?(ns[r].keypoints[a][0]=(ns[r].keypoints[a][0]+t[r].keypoints[a].position.x)/2,ns[r].keypoints[a][1]=(ns[r].keypoints[a][1]+t[r].keypoints[a].position.y)/2,R0(n,ns[r].keypoints[a][0],ns[r].keypoints[a][1])):R0(n,t[r].keypoints[a].position.x,t[r].keypoints[a].position.y);if(ie.drawLabels){n.font=ie.font;for(let a of t[r].keypoints)n.fillStyle=ie.useDepth&&a.position.z?`rgba(${127.5+2*a.position.z}, ${127.5-2*a.position.z}, 255, 0.5)`:ie.color,n.fillText(`${a.part}`,a.position.x+4,a.position.y+4)}if(ie.drawPolygons){let a,s=[];s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),s.length===5&&vg(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftHip"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftKnee"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftAnkle"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftHeel"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftFoot"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),M0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightHip"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightKnee"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightAnkle"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightHeel"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightFoot"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),M0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="leftShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftElbow"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftWrist"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="leftPalm"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),M0(n,s),s.length=0,a=t[r].keypoints.find(i=>i.part==="rightShoulder"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightElbow"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightWrist"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),a=t[r].keypoints.find(i=>i.part==="rightPalm"),a&&a.score>ft.body.scoreThreshold&&s.push([a.position.x,a.position.y]),M0(n,s)}}}}async function E4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=ie.font;for(let r of t){if(ie.drawBoxes&&(n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.useRawBoxes?Kl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Kl(n,r.box[0],r.box[1],r.box[2],r.box[3]),ie.drawLabels&&(ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText("hand",r.box[0]+3,1+r.box[1]+ie.lineHeight,r.box[2])),n.fillStyle=ie.labelColor,n.fillText("hand",r.box[0]+2,0+r.box[1]+ie.lineHeight,r.box[2])),n.stroke()),ie.drawPoints&&r.landmarks&&r.landmarks.length>0)for(let a of r.landmarks)n.fillStyle=ie.useDepth?`rgba(${127.5+2*a[2]}, ${127.5-2*a[2]}, 255, 0.5)`:ie.color,R0(n,a[0],a[1]);if(ie.drawPolygons){let a=s=>{if(!!s)for(let i=0;i<s.length;i++)n.lineWidth=ie.lineWidth,n.beginPath(),n.strokeStyle=ie.useDepth?`rgba(${127.5+2*s[i][2]}, ${127.5-2*s[i][2]}, 255, 0.5)`:ie.color,n.moveTo(s[i>0?i-1:0][0],s[i>0?i-1:0][1]),n.lineTo(s[i][0],s[i][1]),n.stroke()};a(r.annotations.indexFinger),a(r.annotations.middleFinger),a(r.annotations.ringFinger),a(r.annotations.pinky),a(r.annotations.thumb)}}}}async function R4(e,t){if(!t||!e||!(e instanceof HTMLCanvasElement))return;let n=e.getContext("2d");if(!!n){n.lineJoin="round",n.font=ie.font;for(let r of t)if(ie.drawBoxes){if(n.strokeStyle=ie.color,n.fillStyle=ie.color,ie.useRawBoxes?Kl(n,e.width*r.boxRaw[0],e.height*r.boxRaw[1],e.width*r.boxRaw[2],e.height*r.boxRaw[3]):Kl(n,r.box[0],r.box[1],r.box[2],r.box[3]),ie.drawLabels){let a=`${Math.round(100*r.score)}% ${r.label}`;ie.shadowColor&&ie.shadowColor!==""&&(n.fillStyle=ie.shadowColor,n.fillText(a,r.box[0]+3,1+r.box[1]+ie.lineHeight,r.box[2])),n.fillStyle=ie.labelColor,n.fillText(a,r.box[0]+2,0+r.box[1]+ie.lineHeight,r.box[2])}n.stroke()}}}async function ase(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function sse(e,t){!t||!e||e instanceof HTMLCanvasElement&&(T4(e,t.face),C4(e,t.body),E4(e,t.hand),S4(e,t.gesture),R4(e,t.object))}var it=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Uc(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,r)=>(Object.keys(r||{}).forEach(a=>{let s=n[a],i=r[a];Array.isArray(s)&&Array.isArray(i)?n[a]=s.concat(...i):t(s)&&t(i)?n[a]=Uc(s,i):n[a]=i}),n),{})}var F0,Ve,Zl,jc,Hc,Di,Rt,$0,Gc,D0,qc,O0,z0,P0,Ig=class{constructor(t={}){F0.set(this,void 0);Ve.set(this,void 0);Zl.set(this,void 0);jc.set(this,void 0);Hc.set(this,void 0);Di.set(this,void 0);Rt.set(this,(...t)=>{if(!me(this,jc))return;let n=this.tf.engine().state.numTensors,r=me(this,Zl);ta(this,Zl,n);let a=n-r;a!==0&&Ee(...t,a)});$0.set(this,t=>{if(!me(this,Hc))return null;if(!t)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(t instanceof je))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});Gc.set(this,async(t=!1)=>{if(this.config.backend&&this.config.backend!==""&&t||this.tf.getBackend()!==this.config.backend){let n=it();if(this.state="backend",this.config.backend&&this.config.backend!==""){if(this.config.debug&&Ee("setting backend:",this.config.backend),this.config.backend==="wasm"){this.config.debug&&Ee("wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath);let r=await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await this.tf.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");this.config.debug&&Ee(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),r||Ee("warning: wasm simd support is not enabled")}this.config.backend==="humangl"&&w6();try{await this.tf.setBackend(this.config.backend)}catch(r){Ee("error: cannot set backend:",this.config.backend,r)}}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(Ee("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let r=await this.tf.backend().getGPGPUContext().gl;this.config.debug&&Ee(`gl version:${r.getParameter(r.VERSION)} renderer:${r.getParameter(r.RENDERER)}`)}await this.tf.ready(),me(this,Ve).backend=Math.trunc(it()-n)}});D0.set(this,t=>{if(!t||t.length<300)return{roll:null,yaw:null,pitch:null};let n=(s,i,o,l)=>Math.atan2(l-i,o-s),r=s=>Math.abs(s*180/Math.PI%360);return{roll:n(t[33][0],t[33][1],t[263][0],t[263][1]),yaw:n(t[33][0],t[33][2],t[263][0],t[263][2]),pitch:n(t[10][1],t[10][2],t[152][1],t[152][2])}});qc.set(this,async t=>{var c,u,h,d,p,f,m;let n,r,a,s,i,o=[];this.state="run:face",n=it();let l=await((c=this.models.face)==null?void 0:c.estimateFaces(t,this.config));if(me(this,Ve).face=Math.trunc(it()-n),!l)return[];for(let A of l){if(me(this,Rt).call(this,"Get Face"),!A.image||A.image.isDisposedInternal){Ee("Face object is disposed:",A.image);continue}let y=me(this,D0).call(this,A.mesh);me(this,Rt).call(this,"Start Age:"),this.config.async?r=this.config.face.age.enabled?T2(A.image,this.config):{}:(this.state="run:age",n=it(),r=this.config.face.age.enabled?await T2(A.image,this.config):{},me(this,Ve).age=Math.trunc(it()-n)),me(this,Rt).call(this,"Start Gender:"),this.config.async?a=this.config.face.gender.enabled?$2(A.image,this.config):{}:(this.state="run:gender",n=it(),a=this.config.face.gender.enabled?await $2(A.image,this.config):{},me(this,Ve).gender=Math.trunc(it()-n)),me(this,Rt).call(this,"Start Emotion:"),this.config.async?s=this.config.face.emotion.enabled?L2(A.image,this.config):{}:(this.state="run:emotion",n=it(),s=this.config.face.emotion.enabled?await L2(A.image,this.config):{},me(this,Ve).emotion=Math.trunc(it()-n)),me(this,Rt).call(this,"End Emotion:"),me(this,Rt).call(this,"Start Embedding:"),this.config.async?i=this.config.face.embedding.enabled?U2(A,this.config):[]:(this.state="run:embedding",n=it(),i=this.config.face.embedding.enabled?await U2(A,this.config):[],me(this,Ve).embedding=Math.trunc(it()-n)),me(this,Rt).call(this,"End Emotion:"),this.config.async&&([r,a,s,i]=await Promise.all([r,a,s,i])),me(this,Rt).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((u=A==null?void 0:A.annotations)==null?void 0:u.leftEyeIris)&&((h=A==null?void 0:A.annotations)==null?void 0:h.rightEyeIris)&&(delete A.annotations.leftEyeIris,delete A.annotations.rightEyeIris);let g=((d=A.annotations)==null?void 0:d.leftEyeIris)&&((p=A.annotations)==null?void 0:p.rightEyeIris)?11.7*Math.max(Math.abs(A.annotations.leftEyeIris[3][0]-A.annotations.leftEyeIris[1][0]),Math.abs(A.annotations.rightEyeIris[4][1]-A.annotations.rightEyeIris[2][1])):0;o.push({...A,age:r.age,gender:a.gender,genderConfidence:a.confidence,emotion:s,embedding:i,iris:g!==0?Math.trunc(g)/100:0,angle:y,tensor:this.config.face.detector.return?(f=A.image)==null?void 0:f.squeeze():null}),(m=A.image)==null||m.dispose(),me(this,Rt).call(this,"End Face")}return me(this,Rt).call(this,"End FaceMesh:"),this.config.async&&(me(this,Ve).face&&delete me(this,Ve).face,me(this,Ve).age&&delete me(this,Ve).age,me(this,Ve).gender&&delete me(this,Ve).gender,me(this,Ve).emotion&&delete me(this,Ve).emotion),o});O0.set(this,async()=>{let t=(a,s="application/octet-stream")=>fetch(`data:${s};base64,${a}`).then(i=>i.blob()),n,r;switch(this.config.warmup){case"face":n=await t(C0);break;case"full":n=await t(E0);break;default:n=null}if(n){let a=await createImageBitmap(n);r=await this.detect(a,this.config),a.close()}return r});z0.set(this,async()=>new Promise(t=>{let n,r=0;switch(this.config.warmup){case"face":r=256,n="data:image/jpeg;base64,"+C0;break;case"full":case"body":r=1200,n="data:image/jpeg;base64,"+E0;break;default:n=null}let a=new Image;a.onload=async()=>{let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(r,r):document.createElement("canvas");s.width=a.naturalWidth,s.height=a.naturalHeight;let i=s.getContext("2d");i==null||i.drawImage(a,0,0);let o=await this.detect(s,this.config);t(o)},n?a.src=n:t(null)}));P0.set(this,async()=>{let t=i=>Buffer.from(i,"base64"),n=this.config.warmup==="face"?t(C0):t(E0),r=(void 0).decodeJpeg(n),a=r.expandDims(0);this.tf.dispose(r);let s=await this.detect(a,this.config);return this.tf.dispose(a),s});this.tf=xh,this.draw=_g,ta(this,F0,wg),this.version=bg,this.config=Uc(ft,t),this.state="idle",ta(this,Zl,0),ta(this,jc,!1),ta(this,Hc,!1),ta(this,Di,!0),ta(this,Ve,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=n=>xg(n,this.config),this.classes={facemesh:kg,age:N2,gender:C2,emotion:D2,body:this.config.body.modelPath.includes("posenet")?tg:dg,hand:lg,nanodet:mg},this.sysinfo=Wg()}profileData(){return this.config.profile?I2:{}}simmilarity(t,n){return this.config.face.embedding.enabled?B2(t,n):0}enhance(t){return V2(t)}match(t,n,r=0){return M6(t,n,r)}async load(t={}){this.state="load";let n=it();t&&(this.config=Uc(this.config,t)),me(this,Di)&&(this.config.debug&&Ee(`version: ${this.version}`),this.config.debug&&Ee(`tfjs version: ${this.tf.version_core}`),this.config.debug&&Ee("platform:",this.sysinfo.platform),this.config.debug&&Ee("agent:",this.sysinfo.agent),await me(this,Gc).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&Ee("configuration:",this.config),this.config.debug&&Ee("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?kg.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?S2(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?F2(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?P2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?W2(this.config):null),this.models.handpose||(this.config.hand.enabled?hg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?rg(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?pg(this.config):null),this.models.nanodet||(this.config.object.enabled?yg(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await kg.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await S2(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await F2(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await P2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await W2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await hg(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await rg(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await pg(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await yg(this.config))),me(this,Di)&&(this.config.debug&&Ee("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),ta(this,Di,!1));let r=Math.trunc(it()-n);r>(me(this,Ve).load||0)&&(me(this,Ve).load=r)}async detect(t,n={}){return new Promise(async r=>{var f,m,A,y;this.state="config";let a;this.config=Uc(this.config,n),this.state="check";let s=me(this,$0).call(this,t);s&&(Ee(s,t),r({error:s}));let i=it();await me(this,Gc).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),me(this,Rt).call(this,"Start Scope:"),a=it();let o=xg(t,this.config);if(!o||!o.tensor){Ee("could not convert input to tensor"),r({error:"could not convert input to tensor"});return}me(this,Ve).image=Math.trunc(it()-a),me(this,Rt).call(this,"Get Image:");let l,c,u,h;this.config.async?(u=this.config.face.enabled?me(this,qc).call(this,o.tensor):[],me(this,Ve).face&&delete me(this,Ve).face):(this.state="run:face",a=it(),u=this.config.face.enabled?await me(this,qc).call(this,o.tensor):[],me(this,Ve).face=Math.trunc(it()-a)),me(this,Rt).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?(f=this.models.posenet)==null?void 0:f.estimatePoses(o.tensor,this.config):[]:l=this.config.body.enabled?fg(o.tensor,this.config):[],me(this,Ve).body&&delete me(this,Ve).body):(this.state="run:body",a=it(),this.config.body.modelPath.includes("posenet")?l=this.config.body.enabled?await((m=this.models.posenet)==null?void 0:m.estimatePoses(o.tensor,this.config)):[]:l=this.config.body.enabled?await fg(o.tensor,this.config):[],me(this,Ve).body=Math.trunc(it()-a)),me(this,Rt).call(this,"End Body:"),me(this,Rt).call(this,"Start Hand:"),this.config.async?(c=this.config.hand.enabled?(A=this.models.handpose)==null?void 0:A.estimateHands(o.tensor,this.config):[],me(this,Ve).hand&&delete me(this,Ve).hand):(this.state="run:hand",a=it(),c=this.config.hand.enabled?await((y=this.models.handpose)==null?void 0:y.estimateHands(o.tensor,this.config)):[],me(this,Ve).hand=Math.trunc(it()-a)),me(this,Rt).call(this,"End Hand:"),me(this,Rt).call(this,"Start Object:"),this.config.async?(h=this.config.object.enabled?gg(o.tensor,this.config):[],me(this,Ve).object&&delete me(this,Ve).object):(this.state="run:object",a=it(),h=this.config.object.enabled?await gg(o.tensor,this.config):[],me(this,Ve).object=Math.trunc(it()-a)),me(this,Rt).call(this,"End Object:"),this.config.async&&([u,l,c,h]=await Promise.all([u,l,c,h])),o.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),me(this,Rt).call(this,"End Scope:");let d=[];this.config.gesture.enabled&&(a=it(),d=[...o4(u),...i4(l),...u4(c),...l4(u)],this.config.async?me(this,Ve).gesture&&delete me(this,Ve).gesture:me(this,Ve).gesture=Math.trunc(it()-a)),me(this,Ve).total=Math.trunc(it()-i),this.state="idle";let p={face:u,body:l,hand:c,gesture:d,object:h,performance:me(this,Ve),canvas:o.canvas};r(p)})}async warmup(t={}){let n=it();t&&(this.config=Uc(this.config,t));let r=this.config.videoOptimized;this.config.videoOptimized=!1;let a;typeof createImageBitmap=="function"?a=await me(this,O0).call(this):typeof Image!="undefined"?a=await me(this,z0).call(this):a=await me(this,P0).call(this),this.config.videoOptimized=r;let s=it();return this.config.debug&&Ee("Warmup",this.config.warmup,Math.round(s-n),"ms",a),a}};F0=new WeakMap,Ve=new WeakMap,Zl=new WeakMap,jc=new WeakMap,Hc=new WeakMap,Di=new WeakMap,Rt=new WeakMap,$0=new WeakMap,Gc=new WeakMap,D0=new WeakMap,qc=new WeakMap,O0=new WeakMap,z0=new WeakMap,P0=new WeakMap;return ise;})();
 /**
  * @license
  * Copyright 2017 Google LLC. All Rights Reserved.
diff --git a/dist/human.js.map b/dist/human.js.map
index 23bbf745..11685895 100644
--- a/dist/human.js.map
+++ b/dist/human.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
-  "sources": ["../src/blazeface/facemesh.ts", "../src/posenet/keypoints.ts", "../src/human.ts", "../src/log.ts", "../src/sysinfo.ts", "../node_modules/node-fetch/browser.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/alea.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xor128.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xorwow.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xorshift7.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/xor4096.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/lib/tychei.js", "(disabled):crypto", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/seedrandom.js", "../node_modules/@tensorflow/tfjs-core/node_modules/seedrandom/index.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/alea.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xor128.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xorwow.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xorshift7.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/xor4096.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/lib/tychei.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/seedrandom.js", "../node_modules/@tensorflow/tfjs-backend-cpu/node_modules/seedrandom/index.js", "(disabled):path", "(disabled):worker_threads", "(disabled):perf_hooks", "../node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js", "../node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js", "../node_modules/seedrandom/lib/alea.js", "../node_modules/seedrandom/lib/xor128.js", "../node_modules/seedrandom/lib/xorwow.js", "../node_modules/seedrandom/lib/xorshift7.js", "../node_modules/seedrandom/lib/xor4096.js", "../node_modules/seedrandom/lib/tychei.js", "../node_modules/seedrandom/seedrandom.js", "../node_modules/seedrandom/index.js", "../node_modules/string_decoder/lib/string_decoder.js", "../node_modules/@tensorflow/tfjs-core/src/backends/backend.ts", "../node_modules/@tensorflow/tfjs-core/src/util_base.ts", "../node_modules/@tensorflow/tfjs-core/src/environment.ts", "../node_modules/@tensorflow/tfjs-core/src/global_util.ts", "../node_modules/@tensorflow/tfjs-core/src/kernel_names.ts", "../node_modules/@tensorflow/tfjs-core/src/kernel_registry.ts", "../node_modules/@tensorflow/tfjs-core/src/util.ts", "../node_modules/@tensorflow/tfjs-core/src/profiler.ts", "../node_modules/@tensorflow/tfjs-core/src/tape.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor_format.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor_util.ts", "../node_modules/@tensorflow/tfjs-core/src/types.ts", "../node_modules/@tensorflow/tfjs-core/src/engine.ts", "../node_modules/@tensorflow/tfjs-core/src/device_util.ts", "../node_modules/@tensorflow/tfjs-core/src/flags.ts", "../node_modules/@tensorflow/tfjs-core/src/tensor_util_env.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/operation.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/complex.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/tensor_ops_util.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/tensor.ts", "../node_modules/@tensorflow/tfjs-core/src/io/types.ts", "../node_modules/@tensorflow/tfjs-core/src/io/io_utils.ts", "../node_modules/@tensorflow/tfjs-core/src/io/router_registry.ts", "../node_modules/@tensorflow/tfjs-core/src/io/indexed_db.ts", "../node_modules/@tensorflow/tfjs-core/src/io/local_storage.ts", "../node_modules/@tensorflow/tfjs-core/src/io/model_management.ts", "../node_modules/@tensorflow/tfjs-core/src/platforms/platform_browser.ts", "../node_modules/@tensorflow/tfjs-core/src/platforms/platform_node.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/buffer.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/cast.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/clone.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/print.ts", "../node_modules/@tensorflow/tfjs-core/src/base_side_effects.ts", "../node_modules/@tensorflow/tfjs-core/src/io/io.ts", "../node_modules/@tensorflow/tfjs-core/src/io/browser_files.ts", "../node_modules/@tensorflow/tfjs-core/src/io/progress.ts", "../node_modules/@tensorflow/tfjs-core/src/io/weights_loader.ts", "../node_modules/@tensorflow/tfjs-core/src/io/http.ts", "../node_modules/@tensorflow/tfjs-core/src/io/passthrough.ts", "../node_modules/@tensorflow/tfjs-core/src/math.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/mat_mul.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/one_hot.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/transpose.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/confusion_matrix.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/browser.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/tensor3d.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/gather_nd_util.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/scatter_nd_util.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/slice_util.ts", "../node_modules/@tensorflow/tfjs-core/src/serialization.ts", "../node_modules/@tensorflow/tfjs-core/src/test_util.ts", "../node_modules/@tensorflow/tfjs-core/src/version.ts", "../node_modules/@tensorflow/tfjs-core/src/globals.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/add.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/floorDiv.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/div.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/mul.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/abs.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/acos.ts", "../node_modules/@tensorflow/tfjs-core/src/ops/acosh.ts", 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"../node_modules/@tensorflow/tfjs-data/src/iterators/byte_chunk_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/file_chunk_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/iterators/url_chunk_iterator.ts", "../node_modules/@tensorflow/tfjs-data/src/util/source_util.ts", "../node_modules/@tensorflow/tfjs-data/src/sources/file_data_source.ts", "../node_modules/@tensorflow/tfjs-data/src/sources/url_data_source.ts", "../node_modules/@tensorflow/tfjs-data/src/readers.ts", "../node_modules/@tensorflow/tfjs-data/src/version.ts", "../src/tfjs/tf-browser.ts", "../src/tfjs/backend.ts", "../src/blazeface/blazeface.ts", "../src/blazeface/box.ts", "../src/blazeface/util.ts", "../src/blazeface/coords.ts", "../src/blazeface/facepipeline.ts", "../src/age/age.ts", "../src/profile.ts", "../src/gender/gender.ts", "../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/decodePose.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/box.ts", "../src/handpose/handdetector.ts", "../src/handpose/util.ts", "../src/handpose/handpipeline.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/nanodet/nanodet.ts", "../src/gesture/gesture.ts", "../src/imagefx.js", "../src/image.ts", "../config.ts", "../src/sample.ts", "../src/draw.ts"],
-  "sourcesContent": ["import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - prediction.box.startPoint[0],\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - prediction.box.startPoint[1],\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0] / input.shape[2]),\n        Math.max(0, prediction.box.startPoint[1] / input.shape[1]),\n        Math.min(input.shape[1], (prediction.box.endPoint[0]) - prediction.box.startPoint[0]) / input.shape[2],\n        Math.min(input.shape[2], (prediction.box.endPoint[1]) - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        mesh,\n        boxRaw,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      resolve({ face: faceRes, body: bodyRes, hand: handRes, gesture: gestureRes, object: objectRes, performance: this.#perf, canvas: process.canvas });\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 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ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){err(\"requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];var contextAttributes={\"alpha\":!!GROWABLE_HEAP_I32()[a+(0>>2)],\"depth\":!!GROWABLE_HEAP_I32()[a+(4>>2)],\"stencil\":!!GROWABLE_HEAP_I32()[a+(8>>2)],\"antialias\":!!GROWABLE_HEAP_I32()[a+(12>>2)],\"premultipliedAlpha\":!!GROWABLE_HEAP_I32()[a+(16>>2)],\"preserveDrawingBuffer\":!!GROWABLE_HEAP_I32()[a+(20>>2)],\"powerPreference\":__emscripten_webgl_power_preferences[powerPreference],\"failIfMajorPerformanceCaveat\":!!GROWABLE_HEAP_I32()[a+(28>>2)],majorVersion:GROWABLE_HEAP_I32()[a+(32>>2)],minorVersion:GROWABLE_HEAP_I32()[a+(36>>2)],enableExtensionsByDefault:GROWABLE_HEAP_I32()[a+(40>>2)],explicitSwapControl:GROWABLE_HEAP_I32()[a+(44>>2)],proxyContextToMainThread:GROWABLE_HEAP_I32()[a+(48>>2)],renderViaOffscreenBackBuffer:GROWABLE_HEAP_I32()[a+(52>>2)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var 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\"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,HEAPU8,outPtr,maxBytesToWrite)}function writeArrayToMemory(array,buffer){HEAP8.set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;__ATINIT__.push({func:function(){___wasm_call_ctors()}});function preRun(){if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=HEAP32[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){}function _fd_write(fd,iov,iovcnt,pnum){var num=0;for(var i=0;i<iovcnt;i++){var ptr=HEAP32[iov+i*8>>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j])}num+=len}HEAP32[pnum>>2]=num;return 0}var asmLibraryArg={\"a\":_abort,\"d\":_emscripten_memcpy_big,\"e\":_emscripten_resize_heap,\"f\":_fd_close,\"c\":_fd_seek,\"b\":_fd_write};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"h\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"i\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"j\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"k\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"l\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"n\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"o\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"p\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"q\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"r\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"s\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"t\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"u\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"v\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"w\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"x\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"y\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"z\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"F\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var 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_Rsqrt=Module[\"_Rsqrt\"]=function(){return(_Rsqrt=Module[\"_Rsqrt\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var _ScatterNd=Module[\"_ScatterNd\"]=function(){return(_ScatterNd=Module[\"_ScatterNd\"]=Module[\"asm\"][\"qa\"]).apply(null,arguments)};var _SelectV2=Module[\"_SelectV2\"]=function(){return(_SelectV2=Module[\"_SelectV2\"]=Module[\"asm\"][\"ra\"]).apply(null,arguments)};var _Sigmoid=Module[\"_Sigmoid\"]=function(){return(_Sigmoid=Module[\"_Sigmoid\"]=Module[\"asm\"][\"sa\"]).apply(null,arguments)};var _Sin=Module[\"_Sin\"]=function(){return(_Sin=Module[\"_Sin\"]=Module[\"asm\"][\"ta\"]).apply(null,arguments)};var _Softmax=Module[\"_Softmax\"]=function(){return(_Softmax=Module[\"_Softmax\"]=Module[\"asm\"][\"ua\"]).apply(null,arguments)};var _Sqrt=Module[\"_Sqrt\"]=function(){return(_Sqrt=Module[\"_Sqrt\"]=Module[\"asm\"][\"va\"]).apply(null,arguments)};var _Square=Module[\"_Square\"]=function(){return(_Square=Module[\"_Square\"]=Module[\"asm\"][\"wa\"]).apply(null,arguments)};var _SquaredDifference=Module[\"_SquaredDifference\"]=function(){return(_SquaredDifference=Module[\"_SquaredDifference\"]=Module[\"asm\"][\"xa\"]).apply(null,arguments)};var _Step=Module[\"_Step\"]=function(){return(_Step=Module[\"_Step\"]=Module[\"asm\"][\"ya\"]).apply(null,arguments)};var _StridedSlice=Module[\"_StridedSlice\"]=function(){return(_StridedSlice=Module[\"_StridedSlice\"]=Module[\"asm\"][\"za\"]).apply(null,arguments)};var _Sub=Module[\"_Sub\"]=function(){return(_Sub=Module[\"_Sub\"]=Module[\"asm\"][\"Aa\"]).apply(null,arguments)};var _Sum=Module[\"_Sum\"]=function(){return(_Sum=Module[\"_Sum\"]=Module[\"asm\"][\"Ba\"]).apply(null,arguments)};var _Tanh=Module[\"_Tanh\"]=function(){return(_Tanh=Module[\"_Tanh\"]=Module[\"asm\"][\"Ca\"]).apply(null,arguments)};var _Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(e){try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 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0.883246004581451],\n  [0.508952975273132, 0.579437971115112],\n  [0.617941975593567, 0.508316040039062],\n  [0.825608015060425, 0.397674977779388],\n  [0.681214988231659, 0.39623498916626],\n  [0.656635999679565, 0.400596976280212],\n  [0.603900015354156, 0.710216999053955],\n  [0.81208598613739, 0.588539004325867],\n  [0.56801301240921, 0.944564998149872],\n  [0.681007981300354, 0.898285031318665],\n  [0.733752012252808, 0.869701027870178],\n  [0.633830010890961, 0.398822009563446],\n  [0.606792986392975, 0.39553701877594],\n  [0.589659988880157, 0.391062021255493],\n  [0.805015981197357, 0.342108011245728],\n  [0.611334979534149, 0.362284004688263],\n  [0.634037971496582, 0.355970978736877],\n  [0.656635999679565, 0.355356991291046],\n  [0.681214988231659, 0.35834002494812],\n  [0.698584973812103, 0.363156020641327],\n  [0.941866993904114, 0.319076001644135],\n  [0.698584973812103, 0.387449026107788],\n  [0.584177017211914, 0.624107003211975],\n  [0.554318010807037, 0.566076993942261],\n  [0.534153997898102, 0.62064003944397],\n  [0.711217999458313, 0.819975018501282],\n  [0.664629995822906, 0.852871000766754],\n  [0.559099972248077, 0.902631998062134],\n  [0.871706008911133, 0.791940987110138],\n  [0.591234028339386, 0.373893976211548],\n  [0.544341027736664, 0.451583981513977],\n  [0.624562978744507, 0.924192011356354],\n  [0.88577002286911, 0.615028977394104],\n  [0.551338016986847, 0.695277988910675],\n  [0.551980018615723, 0.704632043838501],\n  [0.552887976169586, 0.715808033943176],\n  [0.555167973041534, 0.730794012546539],\n  [0.569944024085999, 0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - prediction.box.topLeft[0],\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - prediction.box.topLeft[1],\n      ] : 0;\n      hands.push({ confidence: prediction.confidence, box, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            boxRaw[0] * outputShape[0],\n            boxRaw[1] * outputShape[1],\n            boxRaw[2] * outputShape[0],\n            boxRaw[3] * outputShape[1],\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n      // rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2] - h.box[0], h.box[3] - h.box[1]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
-  "mappings": 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"../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/decodePose.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/box.ts", "../src/handpose/handdetector.ts", "../src/handpose/util.ts", "../src/handpose/handpipeline.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/nanodet/nanodet.ts", "../src/gesture/gesture.ts", "../src/imagefx.js", "../src/image.ts", "../config.ts", "../src/sample.ts", "../src/draw.ts"],
+  "sourcesContent": ["import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    boxRaw: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.#perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 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Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw 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ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){err(\"requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];var contextAttributes={\"alpha\":!!GROWABLE_HEAP_I32()[a+(0>>2)],\"depth\":!!GROWABLE_HEAP_I32()[a+(4>>2)],\"stencil\":!!GROWABLE_HEAP_I32()[a+(8>>2)],\"antialias\":!!GROWABLE_HEAP_I32()[a+(12>>2)],\"premultipliedAlpha\":!!GROWABLE_HEAP_I32()[a+(16>>2)],\"preserveDrawingBuffer\":!!GROWABLE_HEAP_I32()[a+(20>>2)],\"powerPreference\":__emscripten_webgl_power_preferences[powerPreference],\"failIfMajorPerformanceCaveat\":!!GROWABLE_HEAP_I32()[a+(28>>2)],majorVersion:GROWABLE_HEAP_I32()[a+(32>>2)],minorVersion:GROWABLE_HEAP_I32()[a+(36>>2)],enableExtensionsByDefault:GROWABLE_HEAP_I32()[a+(40>>2)],explicitSwapControl:GROWABLE_HEAP_I32()[a+(44>>2)],proxyContextToMainThread:GROWABLE_HEAP_I32()[a+(48>>2)],renderViaOffscreenBackBuffer:GROWABLE_HEAP_I32()[a+(52>>2)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var 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cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,HEAPU8,outPtr,maxBytesToWrite)}function writeArrayToMemory(array,buffer){HEAP8.set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;__ATINIT__.push({func:function(){___wasm_call_ctors()}});function preRun(){if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=HEAP32[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){}function _fd_write(fd,iov,iovcnt,pnum){var num=0;for(var i=0;i<iovcnt;i++){var ptr=HEAP32[iov+i*8>>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j])}num+=len}HEAP32[pnum>>2]=num;return 0}var asmLibraryArg={\"a\":_abort,\"d\":_emscripten_memcpy_big,\"e\":_emscripten_resize_heap,\"f\":_fd_close,\"c\":_fd_seek,\"b\":_fd_write};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"h\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"i\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"j\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"k\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"l\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"n\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"o\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"p\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"q\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"r\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"s\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"t\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"u\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"v\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"w\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"x\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"y\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"z\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"F\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var 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_Rsqrt=Module[\"_Rsqrt\"]=function(){return(_Rsqrt=Module[\"_Rsqrt\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var _ScatterNd=Module[\"_ScatterNd\"]=function(){return(_ScatterNd=Module[\"_ScatterNd\"]=Module[\"asm\"][\"qa\"]).apply(null,arguments)};var _SelectV2=Module[\"_SelectV2\"]=function(){return(_SelectV2=Module[\"_SelectV2\"]=Module[\"asm\"][\"ra\"]).apply(null,arguments)};var _Sigmoid=Module[\"_Sigmoid\"]=function(){return(_Sigmoid=Module[\"_Sigmoid\"]=Module[\"asm\"][\"sa\"]).apply(null,arguments)};var _Sin=Module[\"_Sin\"]=function(){return(_Sin=Module[\"_Sin\"]=Module[\"asm\"][\"ta\"]).apply(null,arguments)};var _Softmax=Module[\"_Softmax\"]=function(){return(_Softmax=Module[\"_Softmax\"]=Module[\"asm\"][\"ua\"]).apply(null,arguments)};var _Sqrt=Module[\"_Sqrt\"]=function(){return(_Sqrt=Module[\"_Sqrt\"]=Module[\"asm\"][\"va\"]).apply(null,arguments)};var 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(e){try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 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0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: prediction.confidence, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            Math.max(0, (boxRaw[0] * outputShape[0])),\n            Math.max(0, (boxRaw[1] * outputShape[1])),\n            Math.min(1, (boxRaw[2] * outputShape[0]) - (boxRaw[0] * outputShape[0])),\n            Math.min(1, (boxRaw[3] * outputShape[1]) - (boxRaw[1] * outputShape[1])),\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
+  "mappings": 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diff --git a/dist/human.node-gpu.js b/dist/human.node-gpu.js
index f9745899..4700ab46 100644
--- a/dist/human.node-gpu.js
+++ b/dist/human.node-gpu.js
@@ -5,14 +5,14 @@
   author: <https://github.com/vladmandic>'
   */
 
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ln=[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],dn=[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],fn=[33,133,362,263,1,78,308],hr=ln.map(n=>x1[n]),or=dn.map(n=>x1[n]),sr=fn.map(n=>x1[n]);var a1=te.leftEyeLower0,y1=te.rightEyeLower0,me={leftBounds:[a1[0],a1[a1.length-1]],rightBounds:[y1[0],y1[y1.length-1]]},Oe={count:468,mouth:13,symmetryLine:[13,te.midwayBetweenEyes[0]]},L0={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},ue={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function ke(n,e,t,A){for(let r=0;r<i1.length;r++){let{key:c,indices:_}=i1[r],h=te[`${t}${c}`];if(!A||A.includes(c))for(let o=0;o<_.length;o++){let s=_[o];n[h[o]]=[e[s][0],e[s][1],(e[s][2]+n[h[o]][2])/2]}}}var w1=class{constructor(e,t,A){var r,c;this.storedBoxes=[],this.boundingBoxDetector=e,this.meshDetector=t,this.irisModel=A,this.boxSize=((r=e==null?void 0:e.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(t==null?void 0:t.inputs[0].shape[2])||((c=e==null?void 0:e.model)==null?void 0:c.inputs[0].shape[2]),this.irisSize=(A==null?void 0:A.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,t,A,r){let c=be({startPoint:t.startPoint,endPoint:t.endPoint}),_=e.map(i=>[c[0]/this.meshSize*(i[0]-this.meshSize/2),c[1]/this.meshSize*(i[1]-this.meshSize/2),i[2]]),h=A!==0?We(A,[0,0]):je,o=A!==0?_.map(i=>[...V0(i,h),i[2]]):_,s=A!==0?Z0(r):je,a=[...de({startPoint:t.startPoint,endPoint:t.endPoint}),1];return o.map(i=>[i[0]+he(a,s[0]),i[1]+he(a,s[1]),i[2]])}getLeftToRightEyeDepthDifference(e){let t=e[me.leftBounds[0]][2],A=e[me.rightBounds[0]][2];return t-A}getEyeBox(e,t,A,r,c=!1){let _=Se(Ne(this.calculateLandmarksBoundingBox([e[A],e[r]]),this.irisEnlarge)),h=be(_),o=q.image.cropAndResize(t,[[_.startPoint[1]/this.meshSize,_.startPoint[0]/this.meshSize,_.endPoint[1]/this.meshSize,_.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return c&&q.ENV.flags.IS_BROWSER&&(o=q.image.flipLeftRight(o)),{box:_,boxSize:h,crop:o}}getEyeCoords(e,t,A,r=!1){let c=[];for(let _=0;_<ue.numCoordinates;_++){let h=e[_*3],o=e[_*3+1],s=e[_*3+2];c.push([(r?1-h/this.irisSize:h/this.irisSize)*A[0]+t.startPoint[0],o/this.irisSize*A[1]+t.startPoint[1],s])}return{rawCoords:c,iris:c.slice(ue.index)}}getAdjustedIrisCoords(e,t,A){let r=e[te[`${A}EyeUpper0`][ue.upperCenter]][2],c=e[te[`${A}EyeLower0`][ue.lowerCenter]][2],_=(r+c)/2;return t.map((h,o)=>{let s=_;return o===2?s=r:o===4&&(s=c),[h[0],h[1],s]})}async predict(e,t){let A=!1,r;if((this.skipped===0||this.skipped>t.face.detector.skipFrames||!t.face.mesh.enabled||!t.videoOptimized)&&(r=await this.boundingBoxDetector.getBoundingBoxes(e),this.skipped=0),t.videoOptimized&&this.skipped++,r&&r.boxes&&(!t.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==t.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let _ of r.boxes)this.storedBoxes.push({startPoint:_.box.startPoint.dataSync(),endPoint:_.box.endPoint.dataSync(),landmarks:_.landmarks,confidence:_.confidence});this.storedBoxes.length>0&&(A=!0)}if(t.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),A){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let _=0;_<this.storedBoxes.length;_++){let h=O0({startPoint:this.storedBoxes[_].startPoint,endPoint:this.storedBoxes[_].endPoint},r.scaleFactor),o=Ne(h),s=Se(o),a=this.storedBoxes[_].landmarks.arraySync(),i=this.storedBoxes[_].confidence;this.storedBoxes[_]={...s,confidence:i,landmarks:a}}}r&&r.boxes&&r.boxes.forEach(_=>{_.box.startPoint.dispose(),_.box.endPoint.dispose(),_.landmarks.dispose()});let c=q.tidy(()=>this.storedBoxes.map((_,h)=>{let o=_.confidence,s,a=0,i;if(t.face.detector.rotation&&t.face.mesh.enabled&&q.ENV.flags.IS_BROWSER){let[p,y]=_.landmarks.length>=Oe.count?Oe.symmetryLine:L0.symmetryLine;a=s1(_.landmarks[p],_.landmarks[y]);let m=de({startPoint:_.startPoint,endPoint:_.endPoint}),z=[m[0]/e.shape[2],m[1]/e.shape[1]],E=q.image.rotateWithOffset(e,a,0,z);i=We(-a,m),t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{i=je;let p=e.clone();t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},p,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},p,[this.boxSize,this.boxSize]).div(255)}if(!t.face.mesh.enabled)return{coords:null,box:_,faceConfidence:null,boxConfidence:_.confidence,confidence:_.confidence,image:s};let[,l,d]=this.meshDetector.predict(s),f=l.dataSync()[0];if(f<t.face.detector.minConfidence)return null;let b=q.reshape(d,[-1,3]).arraySync();if(t.face.iris.enabled){let{box:p,boxSize:y,crop:m}=this.getEyeBox(b,s,me.leftBounds[0],me.leftBounds[1],!0),{box:z,boxSize:E,crop:L}=this.getEyeBox(b,s,me.rightBounds[0],me.rightBounds[1]),b0=this.irisModel.predict(q.concat([m,L])).dataSync(),Yt=b0.slice(0,ue.numCoordinates*3),{rawCoords:g0,iris:Bt}=this.getEyeCoords(Yt,p,y,!0),Jt=b0.slice(ue.numCoordinates*3),{rawCoords:T0,iris:Kt}=this.getEyeCoords(Jt,z,E),P0=this.getLeftToRightEyeDepthDifference(b);Math.abs(P0)<30?(ke(b,g0,"left",null),ke(b,T0,"right",null)):P0<1?ke(b,g0,"left",["EyeUpper0","EyeLower0"]):ke(b,T0,"right",["EyeUpper0","EyeLower0"]);let Ut=this.getAdjustedIrisCoords(b,Bt,"left"),Dt=this.getAdjustedIrisCoords(b,Kt,"right");b=b.concat(Ut).concat(Dt)}let k=this.transformRawCoords(b,_,a,i);_=Ne(this.calculateLandmarksBoundingBox(k),1.5);let I=q.tensor2d(k);if(t.face.detector.rotation&&t.face.mesh.enabled&&t.face.detector.return&&q.ENV.flags.IS_BROWSER){let[p,y]=_.landmarks.length>=Oe.count?Oe.symmetryLine:L0.symmetryLine;a=s1(_.landmarks[p],_.landmarks[y]);let m=de({startPoint:_.startPoint,endPoint:_.endPoint}),z=[m[0]/e.shape[2],m[1]/e.shape[1]],E=q.image.rotateWithOffset(e,a,0,z);i=We(-a,m),s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let M={coords:I,box:_,faceConfidence:f,boxConfidence:o,image:s,rawCoords:b},B=Se(_);return this.storedBoxes[h]={...B,landmarks:k,confidence:_.confidence,faceConfidence:f},M}));return c=c.filter(_=>_!==null),t.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(_=>_.faceConfidence>t.face.detector.minConfidence)),this.detectedFaces=c.length,c}calculateLandmarksBoundingBox(e){let t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c,landmarks:e}}};var u0=j(X0());var m1={};U(m1,{load:()=>u1,predict:()=>p1});var ne=j(Z());var f1={};function D(n,e){if(!e||!e.kernels)return;let t=5,A=e.kernels.filter(h=>h.kernelTimeMs>0).reduce((h,o)=>h+=o.kernelTimeMs,0),r=e.kernels.map((h,o)=>(h.id=o,h)).filter(h=>h.kernelTimeMs>0).sort((h,o)=>o.kernelTimeMs-h.kernelTimeMs),c=e.kernels.map((h,o)=>(h.id=o,h)).filter(h=>h.totalBytesSnapshot>0).sort((h,o)=>o.totalBytesSnapshot-h.totalBytesSnapshot);r.length>t&&(r.length=t),c.length>t&&(c.length=t);let _={newBytes:e.newBytes,newTensors:e.newTensors,peakBytes:e.peakBytes,numKernelOps:e.kernels.length,timeKernelOps:A,slowestKernelOps:r,largestKernelOps:c};f1[n]=_,g("Human profiler",n,_)}var oe,Ie={age:0},Ze=Number.MAX_SAFE_INTEGER;async function u1(n){return oe||(oe=await ne.loadGraphModel(n.face.age.modelPath),n.debug&&g(`load model: ${n.face.age.modelPath.match(/\/(.*)\./)[1]}`)),oe}async function p1(n,e){return 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ce?Ve<e.face.gender.skipFrames&&e.videoOptimized&&g1.gender!==""?(Ve++,g1):(e.videoOptimized?Ve=0:Ve=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=H.image.resizeBilinear(n,[ce.inputs[0].shape[2],ce.inputs[0].shape[1]],!1),r;T1?r=H.tidy(()=>{let[h,o,s]=H.split(A,3,3),a=H.mul(h,P1[0]),i=H.mul(o,P1[1]),l=H.mul(s,P1[2]);return H.addN([a,i,l]).sub(.5).mul(2)}):r=H.mul(A,[255]),H.dispose(A);let c,_={gender:"",confidence:0};if(!e.profile)e.face.gender.enabled&&(c=await ce.predict(r));else{let h=e.face.gender.enabled?await H.profile(()=>ce.predict(r)):{};c=h.result.clone(),h.result.dispose(),D("gender",h)}if(r.dispose(),c){let h=c.dataSync();if(T1)(h[0]>e.face.gender.minConfidence||h[1]>e.face.gender.minConfidence)&&(_.gender=h[0]>h[1]?"female":"male",_.confidence=h[0]>h[1]?Math.trunc(100*h[0])/100:Math.trunc(100*h[1])/100);else{let o=Math.trunc(200*Math.abs(h[0]-.5))/100;o>e.face.gender.minConfidence&&(_.gender=h[0]<=.5?"female":"male",_.confidence=Math.min(.99,o))}}c.dispose(),g1=_,t(_)})):null}var M1={};U(M1,{load:()=>N1,predict:()=>S1});var X=j(Z());var un=["angry","disgust","fear","happy","sad","surprise","neutral"],se,R1=[],Le=Number.MAX_SAFE_INTEGER,E1=[.2989,.587,.114];async function N1(n){return se||(se=await X.loadGraphModel(n.face.emotion.modelPath),n.debug&&g(`load model: ${n.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),se}async function S1(n,e){return se?Le<e.face.emotion.skipFrames&&e.videoOptimized&&R1.length>0?(Le++,R1):(e.videoOptimized?Le=0:Le=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=X.image.resizeBilinear(n,[se.inputs[0].shape[2],se.inputs[0].shape[1]],!1),[r,c,_]=X.split(A,3,3);A.dispose();let h=X.mul(r,E1[0]),o=X.mul(c,E1[1]),s=X.mul(_,E1[2]);r.dispose(),c.dispose(),_.dispose();let a=X.addN([h,o,s]);h.dispose(),o.dispose(),s.dispose();let i=X.tidy(()=>a.sub(.5).mul(2));a.dispose();let l=[];if(e.face.emotion.enabled){let d;if(e.profile){let f=await X.profile(()=>se.predict(i));d=f.result.dataSync(),f.result.dispose(),D("emotion",f)}else{let f=await se.predict(i);d=f.dataSync(),X.dispose(f)}for(let f=0;f<d.length;f++)d[f]>e.face.emotion.minConfidence&&l.push({score:Math.min(.99,Math.trunc(100*d[f])/100),emotion:un[f]});l.sort((f,x)=>x.score-f.score)}i.dispose(),R1=l,t(l)})):null}var N=j(Z());var re;async function j1(n){return re||(re=await N.loadGraphModel(n.face.embedding.modelPath),n.debug&&g(`load model: ${n.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),re}function W1(n,e,t=2){if(!n||!e||(n==null?void 0:n.length)===0||(e==null?void 0:e.length)===0||(n==null?void 0:n.length)!==(e==null?void 0:e.length))return 0;let A=n.map((c,_)=>Math.abs(n[_]-e[_])**t).reduce((c,_)=>c+_,0)**(1/t);return Math.max(Math.trunc(1e3*(1-A))/1e3,0)}function F0(n,e,t=0){let A={simmilarity:0,name:"",source:"",embedding:[]};if(!n||!e||!Array.isArray(n)||!Array.isArray(e))return A;for(let r of e)if(r.embedding&&r.name){let c=W1(n,r.embedding);c>t&&c>A.simmilarity&&(A={...r,simmilarity:c})}return A}function O1(n){return N.tidy(()=>{let t=[[.05,.15,.85,.85]],A=n.image||n.tensor;if(!(A instanceof N.Tensor))return null;let r=A.shape.length===3?N.image.cropAndResize(N.expandDims(A,0),t,[0],[re.inputs[0].shape[2],re.inputs[0].shape[1]]):N.image.cropAndResize(A,t,[0],[re.inputs[0].shape[2],re.inputs[0].shape[1]]),c=[.2989,.587,.114],[_,h,o]=N.split(r,3,3),s=N.mul(_,c[0]),a=N.mul(h,c[1]),i=N.mul(o,c[2]),l=N.addN([s,a,i]),d=N.stack([l,l,l],3).squeeze(4),f=d.sub(d.min());return f.div(f.max())})}async function k1(n,e){return re?new Promise(async t=>{let A=[];if(e.face.embedding.enabled){let r=O1(n);if(!e.profile)A=N.tidy(()=>[...re.predict(r).reshape([128,2]).logSumExp(1).dataSync()]);else{let c=await 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t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c}}};var dt=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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ft=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],mt=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var G;async function _0(n){return G||(G=await xe.loadGraphModel(n.body.modelPath),G.width=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[2].size),G.height=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[1].size),n.debug&&g(`load model: ${n.body.modelPath.match(/\/(.*)\./)[1]}`)),G}async function h0(n,e){if(!G||!e.body.enabled)return null;let t={width:n.shape[2],height:n.shape[1]},A=xe.image.resizeBilinear(n,[G.width,G.height],!1),r=xe.div(A,[255]);A.dispose();let c;if(e.profile){let s=await xe.profile(()=>G.predict(r));c=s.result.find(a=>a.size===195||a.size===155).dataSync(),s.result.forEach(a=>a.dispose()),D("blazepose",s)}else{let s=await G.predict(r);c=s.find(a=>a.size===195||a.size===155).dataSync(),s.forEach(a=>a.dispose())}r.dispose();let _=[],h=c.length===195?ft:mt,o=5;for(let 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ln=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],dn=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],fn=[33,133,362,263,1,78,308],hr=ln.map(n=>a1[n]),or=dn.map(n=>a1[n]),sr=fn.map(n=>a1[n]);var y1=te.leftEyeLower0,w1=te.rightEyeLower0,me={leftBounds:[y1[0],y1[y1.length-1]],rightBounds:[w1[0],w1[w1.length-1]]},ke={count:468,mouth:13,symmetryLine:[13,te.midwayBetweenEyes[0]]},Vt={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},ue={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function Ie(n,e,t,A){for(let r=0;r<x1.length;r++){let{key:c,indices:_}=x1[r],h=te[`${t}${c}`];if(!A||A.includes(c))for(let o=0;o<_.length;o++){let s=_[o];n[h[o]]=[e[s][0],e[s][1],(e[s][2]+n[h[o]][2])/2]}}}var l1=class{constructor(e,t,A){var r,c;this.storedBoxes=[],this.boundingBoxDetector=e,this.meshDetector=t,this.irisModel=A,this.boxSize=((r=e==null?void 0:e.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(t==null?void 0:t.inputs[0].shape[2])||((c=e==null?void 0:e.model)==null?void 0:c.inputs[0].shape[2]),this.irisSize=(A==null?void 0:A.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,t,A,r){let c=ge({startPoint:t.startPoint,endPoint:t.endPoint}),_=e.map(i=>[c[0]/this.meshSize*(i[0]-this.meshSize/2),c[1]/this.meshSize*(i[1]-this.meshSize/2),i[2]]),h=A!==0?Oe(A,[0,0]):We,o=A!==0?_.map(i=>[...Lt(i,h),i[2]]):_,s=A!==0?Zt(r):We,a=[...de({startPoint:t.startPoint,endPoint:t.endPoint}),1];return o.map(i=>[i[0]+he(a,s[0]),i[1]+he(a,s[1]),i[2]])}getLeftToRightEyeDepthDifference(e){let t=e[me.leftBounds[0]][2],A=e[me.rightBounds[0]][2];return t-A}getEyeBox(e,t,A,r,c=!1){let _=je(Se(this.calculateLandmarksBoundingBox([e[A],e[r]]),this.irisEnlarge)),h=ge(_),o=q.image.cropAndResize(t,[[_.startPoint[1]/this.meshSize,_.startPoint[0]/this.meshSize,_.endPoint[1]/this.meshSize,_.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return c&&q.ENV.flags.IS_BROWSER&&(o=q.image.flipLeftRight(o)),{box:_,boxSize:h,crop:o}}getEyeCoords(e,t,A,r=!1){let c=[];for(let _=0;_<ue.numCoordinates;_++){let h=e[_*3],o=e[_*3+1],s=e[_*3+2];c.push([(r?1-h/this.irisSize:h/this.irisSize)*A[0]+t.startPoint[0],o/this.irisSize*A[1]+t.startPoint[1],s])}return{rawCoords:c,iris:c.slice(ue.index)}}getAdjustedIrisCoords(e,t,A){let r=e[te[`${A}EyeUpper0`][ue.upperCenter]][2],c=e[te[`${A}EyeLower0`][ue.lowerCenter]][2],_=(r+c)/2;return t.map((h,o)=>{let s=_;return o===2?s=r:o===4&&(s=c),[h[0],h[1],s]})}async predict(e,t){let A=!1,r;if((this.skipped===0||this.skipped>t.face.detector.skipFrames||!t.face.mesh.enabled||!t.videoOptimized)&&(r=await this.boundingBoxDetector.getBoundingBoxes(e),this.skipped=0),t.videoOptimized&&this.skipped++,r&&r.boxes&&(!t.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==t.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let _ of r.boxes)this.storedBoxes.push({startPoint:_.box.startPoint.dataSync(),endPoint:_.box.endPoint.dataSync(),landmarks:_.landmarks,confidence:_.confidence});this.storedBoxes.length>0&&(A=!0)}if(t.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),A){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let _=0;_<this.storedBoxes.length;_++){let h=Ot({startPoint:this.storedBoxes[_].startPoint,endPoint:this.storedBoxes[_].endPoint},r.scaleFactor),o=Se(h),s=je(o),a=this.storedBoxes[_].landmarks.arraySync(),i=this.storedBoxes[_].confidence;this.storedBoxes[_]={...s,confidence:i,landmarks:a}}}r&&r.boxes&&r.boxes.forEach(_=>{_.box.startPoint.dispose(),_.box.endPoint.dispose(),_.landmarks.dispose()});let c=q.tidy(()=>this.storedBoxes.map((_,h)=>{let o=_.confidence,s,a=0,i;if(t.face.detector.rotation&&t.face.mesh.enabled&&q.ENV.flags.IS_BROWSER){let[p,w]=_.landmarks.length>=ke.count?ke.symmetryLine:Vt.symmetryLine;a=i1(_.landmarks[p],_.landmarks[w]);let d=de({startPoint:_.startPoint,endPoint:_.endPoint}),z=[d[0]/e.shape[2],d[1]/e.shape[1]],E=q.image.rotateWithOffset(e,a,0,z);i=Oe(-a,d),t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{i=We;let p=e.clone();t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},p,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},p,[this.boxSize,this.boxSize]).div(255)}if(!t.face.mesh.enabled)return{coords:null,box:_,faceConfidence:null,boxConfidence:_.confidence,confidence:_.confidence,image:s};let[,l,m]=this.meshDetector.predict(s),f=l.dataSync()[0];if(f<t.face.detector.minConfidence)return null;let b=q.reshape(m,[-1,3]).arraySync();if(t.face.iris.enabled){let{box:p,boxSize:w,crop:d}=this.getEyeBox(b,s,me.leftBounds[0],me.leftBounds[1],!0),{box:z,boxSize:E,crop:V}=this.getEyeBox(b,s,me.rightBounds[0],me.rightBounds[1]),bt=this.irisModel.predict(q.concat([d,V])).dataSync(),Y0=bt.slice(0,ue.numCoordinates*3),{rawCoords:gt,iris:J0}=this.getEyeCoords(Y0,p,w,!0),C0=bt.slice(ue.numCoordinates*3),{rawCoords:Tt,iris:K0}=this.getEyeCoords(C0,z,E),Pt=this.getLeftToRightEyeDepthDifference(b);Math.abs(Pt)<30?(Ie(b,gt,"left",null),Ie(b,Tt,"right",null)):Pt<1?Ie(b,gt,"left",["EyeUpper0","EyeLower0"]):Ie(b,Tt,"right",["EyeUpper0","EyeLower0"]);let U0=this.getAdjustedIrisCoords(b,J0,"left"),D0=this.getAdjustedIrisCoords(b,K0,"right");b=b.concat(U0).concat(D0)}let j=this.transformRawCoords(b,_,a,i);_=Se(this.calculateLandmarksBoundingBox(j),1.5);let I=q.tensor2d(j);if(t.face.detector.rotation&&t.face.mesh.enabled&&t.face.detector.return&&q.ENV.flags.IS_BROWSER){let[p,w]=_.landmarks.length>=ke.count?ke.symmetryLine:Vt.symmetryLine;a=i1(_.landmarks[p],_.landmarks[w]);let d=de({startPoint:_.startPoint,endPoint:_.endPoint}),z=[d[0]/e.shape[2],d[1]/e.shape[1]],E=q.image.rotateWithOffset(e,a,0,z);i=Oe(-a,d),s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let R={coords:I,box:_,faceConfidence:f,boxConfidence:o,image:s,rawCoords:b},J=je(_);return this.storedBoxes[h]={...J,landmarks:j,confidence:_.confidence,faceConfidence:f},R}));return c=c.filter(_=>_!==null),t.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(_=>_.faceConfidence>t.face.detector.minConfidence)),this.detectedFaces=c.length,c}calculateLandmarksBoundingBox(e){let t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c,landmarks:e}}};var ut=W(Xt());var u1={};U(u1,{load:()=>p1,predict:()=>b1});var ne=W(Z());var m1={};function D(n,e){if(!e||!e.kernels)return;let t=5,A=e.kernels.filter(h=>h.kernelTimeMs>0).reduce((h,o)=>h+=o.kernelTimeMs,0),r=e.kernels.map((h,o)=>(h.id=o,h)).filter(h=>h.kernelTimeMs>0).sort((h,o)=>o.kernelTimeMs-h.kernelTimeMs),c=e.kernels.map((h,o)=>(h.id=o,h)).filter(h=>h.totalBytesSnapshot>0).sort((h,o)=>o.totalBytesSnapshot-h.totalBytesSnapshot);r.length>t&&(r.length=t),c.length>t&&(c.length=t);let _={newBytes:e.newBytes,newTensors:e.newTensors,peakBytes:e.peakBytes,numKernelOps:e.kernels.length,timeKernelOps:A,slowestKernelOps:r,largestKernelOps:c};m1[n]=_,g("Human profiler",n,_)}var oe,Ze={age:0},Le=Number.MAX_SAFE_INTEGER;async function p1(n){return oe||(oe=await ne.loadGraphModel(n.face.age.modelPath),n.debug&&g(`load model: ${n.face.age.modelPath.match(/\/(.*)\./)[1]}`)),oe}async function b1(n,e){return oe?Le<e.face.age.skipFrames&&e.videoOptimized&&Ze.age&&Ze.age>0?(Le++,Ze):(e.videoOptimized?Le=0:Le=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=ne.image.resizeBilinear(n,[oe.inputs[0].shape[2],oe.inputs[0].shape[1]],!1),r=ne.mul(A,[255]);ne.dispose(A);let c,_={age:0};if(!e.profile)e.face.age.enabled&&(c=await oe.predict(r));else{let h=e.face.age.enabled?await ne.profile(()=>oe.predict(r)):{};c=h.result.clone(),h.result.dispose(),D("age",h)}if(r.dispose(),c){let h=c.dataSync();_.age=Math.trunc(10*h[0])/10}c.dispose(),Ze=_,t(_)})):null}var g1={};U(g1,{load:()=>z1,predict:()=>R1});var H=W(Z());var ce,T1={gender:""},Ve=Number.MAX_SAFE_INTEGER,P1=!1,v1=[.2989,.587,.114];async function z1(n){return ce||(ce=await H.loadGraphModel(n.face.gender.modelPath),P1=ce.inputs[0].shape[3]===1,n.debug&&g(`load model: ${n.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),ce}async function R1(n,e){return ce?Ve<e.face.gender.skipFrames&&e.videoOptimized&&T1.gender!==""?(Ve++,T1):(e.videoOptimized?Ve=0:Ve=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=H.image.resizeBilinear(n,[ce.inputs[0].shape[2],ce.inputs[0].shape[1]],!1),r;P1?r=H.tidy(()=>{let[h,o,s]=H.split(A,3,3),a=H.mul(h,v1[0]),i=H.mul(o,v1[1]),l=H.mul(s,v1[2]);return H.addN([a,i,l]).sub(.5).mul(2)}):r=H.mul(A,[255]),H.dispose(A);let c,_={gender:"",confidence:0};if(!e.profile)e.face.gender.enabled&&(c=await ce.predict(r));else{let h=e.face.gender.enabled?await H.profile(()=>ce.predict(r)):{};c=h.result.clone(),h.result.dispose(),D("gender",h)}if(r.dispose(),c){let h=c.dataSync();if(P1)(h[0]>e.face.gender.minConfidence||h[1]>e.face.gender.minConfidence)&&(_.gender=h[0]>h[1]?"female":"male",_.confidence=h[0]>h[1]?Math.trunc(100*h[0])/100:Math.trunc(100*h[1])/100);else{let o=Math.trunc(200*Math.abs(h[0]-.5))/100;o>e.face.gender.minConfidence&&(_.gender=h[0]<=.5?"female":"male",_.confidence=Math.min(.99,o))}}c.dispose(),T1=_,t(_)})):null}var M1={};U(M1,{load:()=>S1,predict:()=>j1});var X=W(Z());var un=["angry","disgust","fear","happy","sad","surprise","neutral"],se,E1=[],He=Number.MAX_SAFE_INTEGER,N1=[.2989,.587,.114];async function S1(n){return se||(se=await X.loadGraphModel(n.face.emotion.modelPath),n.debug&&g(`load model: ${n.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),se}async function j1(n,e){return se?He<e.face.emotion.skipFrames&&e.videoOptimized&&E1.length>0?(He++,E1):(e.videoOptimized?He=0:He=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=X.image.resizeBilinear(n,[se.inputs[0].shape[2],se.inputs[0].shape[1]],!1),[r,c,_]=X.split(A,3,3);A.dispose();let h=X.mul(r,N1[0]),o=X.mul(c,N1[1]),s=X.mul(_,N1[2]);r.dispose(),c.dispose(),_.dispose();let a=X.addN([h,o,s]);h.dispose(),o.dispose(),s.dispose();let i=X.tidy(()=>a.sub(.5).mul(2));a.dispose();let l=[];if(e.face.emotion.enabled){let m;if(e.profile){let f=await X.profile(()=>se.predict(i));m=f.result.dataSync(),f.result.dispose(),D("emotion",f)}else{let f=await se.predict(i);m=f.dataSync(),X.dispose(f)}for(let f=0;f<m.length;f++)m[f]>e.face.emotion.minConfidence&&l.push({score:Math.min(.99,Math.trunc(100*m[f])/100),emotion:un[f]});l.sort((f,x)=>x.score-f.score)}i.dispose(),E1=l,t(l)})):null}var N=W(Z());var re;async function W1(n){return re||(re=await N.loadGraphModel(n.face.embedding.modelPath),n.debug&&g(`load model: ${n.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),re}function O1(n,e,t=2){if(!n||!e||(n==null?void 0:n.length)===0||(e==null?void 0:e.length)===0||(n==null?void 0:n.length)!==(e==null?void 0:e.length))return 0;let A=n.map((c,_)=>Math.abs(n[_]-e[_])**t).reduce((c,_)=>c+_,0)**(1/t);return Math.max(Math.trunc(1e3*(1-A))/1e3,0)}function Ft(n,e,t=0){let A={simmilarity:0,name:"",source:"",embedding:[]};if(!n||!e||!Array.isArray(n)||!Array.isArray(e))return A;for(let r of e)if(r.embedding&&r.name){let c=O1(n,r.embedding);c>t&&c>A.simmilarity&&(A={...r,simmilarity:c})}return A}function k1(n){return N.tidy(()=>{let t=[[.05,.15,.85,.85]],A=n.image||n.tensor;if(!(A instanceof N.Tensor))return null;let r=A.shape.length===3?N.image.cropAndResize(N.expandDims(A,0),t,[0],[re.inputs[0].shape[2],re.inputs[0].shape[1]]):N.image.cropAndResize(A,t,[0],[re.inputs[0].shape[2],re.inputs[0].shape[1]]),c=[.2989,.587,.114],[_,h,o]=N.split(r,3,3),s=N.mul(_,c[0]),a=N.mul(h,c[1]),i=N.mul(o,c[2]),l=N.addN([s,a,i]),m=N.stack([l,l,l],3).squeeze(4),f=m.sub(m.min());return f.div(f.max())})}async function I1(n,e){return re?new Promise(async t=>{let A=[];if(e.face.embedding.enabled){let r=k1(n);if(!e.profile)A=N.tidy(()=>[...re.predict(r).reshape([128,2]).logSumExp(1).dataSync()]);else{let c=await 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t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c}}};var d0=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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f0=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],m0=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var G;async function ht(n){return G||(G=await xe.loadGraphModel(n.body.modelPath),G.width=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[2].size),G.height=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[1].size),n.debug&&g(`load model: ${n.body.modelPath.match(/\/(.*)\./)[1]}`)),G}async function ot(n,e){if(!G||!e.body.enabled)return null;let t={width:n.shape[2],height:n.shape[1]},A=xe.image.resizeBilinear(n,[G.width,G.height],!1),r=xe.div(A,[255]);A.dispose();let c;if(e.profile){let s=await xe.profile(()=>G.predict(r));c=s.result.find(a=>a.size===195||a.size===155).dataSync(),s.result.forEach(a=>a.dispose()),D("blazepose",s)}else{let s=await G.predict(r);c=s.find(a=>a.size===195||a.size===155).dataSync(),s.forEach(a=>a.dispose())}r.dispose();let _=[],h=c.length===195?f0:m0,o=5;for(let 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r,c=[];c.length=0,r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightHip"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftHip"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),c.length===5&&f0(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="leftHip"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftKnee"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftAnkle"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftHeel"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftFoot"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),$e(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="rightHip"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightKnee"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightAnkle"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightHeel"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightFoot"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),$e(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftElbow"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftWrist"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftPalm"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),$e(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightElbow"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightWrist"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightPalm"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),$e(t,c)}}}}async function qt(n,e){if(!e||!n||!(n instanceof HTMLCanvasElement))return;let t=n.getContext("2d");if(!!t){t.lineJoin="round",t.font=w.font;for(let A of e){if(w.drawBoxes&&(t.strokeStyle=w.color,t.fillStyle=w.color,d0(t,A.box[0],A.box[1],A.box[2],A.box[3]),w.drawLabels&&(w.shadowColor&&w.shadowColor!==""&&(t.fillStyle=w.shadowColor,t.fillText("hand",A.box[0]+3,1+A.box[1]+w.lineHeight,A.box[2])),t.fillStyle=w.labelColor,t.fillText("hand",A.box[0]+2,0+A.box[1]+w.lineHeight,A.box[2])),t.stroke()),w.drawPoints&&A.landmarks&&A.landmarks.length>0)for(let r of A.landmarks)t.fillStyle=w.useDepth?`rgba(${127.5+2*r[2]}, ${127.5-2*r[2]}, 255, 0.5)`:w.color,Qe(t,r[0],r[1]);if(w.drawPolygons){let r=c=>{if(!!c)for(let _=0;_<c.length;_++)t.lineWidth=w.lineWidth,t.beginPath(),t.strokeStyle=w.useDepth?`rgba(${127.5+2*c[_][2]}, ${127.5-2*c[_][2]}, 255, 0.5)`:w.color,t.moveTo(c[_>0?_-1:0][0],c[_>0?_-1:0][1]),t.lineTo(c[_][0],c[_][1]),t.stroke()};r(A.annotations.indexFinger),r(A.annotations.middleFinger),r(A.annotations.ringFinger),r(A.annotations.pinky),r(A.annotations.thumb)}}}}async function Ct(n,e){if(!e||!n||!(n instanceof HTMLCanvasElement))return;let t=n.getContext("2d");if(!!t){t.lineJoin="round",t.font=w.font;for(let A of e)if(w.drawBoxes){if(t.strokeStyle=w.color,t.fillStyle=w.color,d0(t,A.box[0],A.box[1],A.box[2]-A.box[0],A.box[3]-A.box[1]),w.drawLabels){let r=`${Math.round(100*A.score)}% ${A.label}`;w.shadowColor&&w.shadowColor!==""&&(t.fillStyle=w.shadowColor,t.fillText(r,A.box[0]+3,1+A.box[1]+w.lineHeight,A.box[2])),t.fillStyle=w.labelColor,t.fillText(r,A.box[0]+2,0+A.box[1]+w.lineHeight,A.box[2])}t.stroke()}}}async function Jn(n,e){if(!n||!e||!(n instanceof HTMLCanvasElement)||!(e instanceof HTMLCanvasElement))return;let t=n.getContext("2d");t==null||t.drawImage(n,0,0)}async function Kn(n,e){!e||!n||n instanceof HTMLCanvasElement&&(Xt(n,e.face),Ft(n,e.body),qt(n,e.hand),Ht(n,e.gesture),Ct(n,e.object))}var R=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Te(...n){let e=t=>t&&typeof t=="object";return n.reduce((t,A)=>(Object.keys(A||{}).forEach(r=>{let c=t[r],_=A[r];Array.isArray(c)&&Array.isArray(_)?t[r]=c.concat(..._):e(c)&&e(_)?t[r]=Te(c,_):t[r]=_}),t),{})}var e1,P,pe,Pe,ve,le,O,t1,ze,n1,Me,r1,A1,c1,p0=class{constructor(e={}){e1.set(this,void 0);P.set(this,void 0);pe.set(this,void 0);Pe.set(this,void 0);ve.set(this,void 0);le.set(this,void 0);O.set(this,(...e)=>{if(!u(this,Pe))return;let t=this.tf.engine().state.numTensors,A=u(this,pe);Ae(this,pe,t);let r=t-A;r!==0&&g(...e,r)});t1.set(this,e=>{if(!u(this,ve))return null;if(!e)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(e instanceof m0.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(t){return"backend not loaded"}return 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k=u(this,n1).call(this,b.mesh);u(this,O).call(this,"Start Age:"),this.config.async?A=this.config.face.age.enabled?p1(b.image,this.config):{}:(this.state="run:age",t=R(),A=this.config.face.age.enabled?await p1(b.image,this.config):{},u(this,P).age=Math.trunc(R()-t)),u(this,O).call(this,"Start Gender:"),this.config.async?r=this.config.face.gender.enabled?z1(b.image,this.config):{}:(this.state="run:gender",t=R(),r=this.config.face.gender.enabled?await z1(b.image,this.config):{},u(this,P).gender=Math.trunc(R()-t)),u(this,O).call(this,"Start Emotion:"),this.config.async?c=this.config.face.emotion.enabled?S1(b.image,this.config):{}:(this.state="run:emotion",t=R(),c=this.config.face.emotion.enabled?await S1(b.image,this.config):{},u(this,P).emotion=Math.trunc(R()-t)),u(this,O).call(this,"End Emotion:"),u(this,O).call(this,"Start Embedding:"),this.config.async?_=this.config.face.embedding.enabled?k1(b,this.config):[]:(this.state="run:embedding",t=R(),_=this.config.face.embedding.enabled?await k1(b,this.config):[],u(this,P).embedding=Math.trunc(R()-t)),u(this,O).call(this,"End Emotion:"),this.config.async&&([A,r,c,_]=await Promise.all([A,r,c,_])),u(this,O).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((a=b==null?void 0:b.annotations)==null?void 0:a.leftEyeIris)&&((i=b==null?void 0:b.annotations)==null?void 0:i.rightEyeIris)&&(delete b.annotations.leftEyeIris,delete b.annotations.rightEyeIris);let I=((l=b.annotations)==null?void 0:l.leftEyeIris)&&((d=b.annotations)==null?void 0:d.rightEyeIris)?11.7*Math.max(Math.abs(b.annotations.leftEyeIris[3][0]-b.annotations.leftEyeIris[1][0]),Math.abs(b.annotations.rightEyeIris[4][1]-b.annotations.rightEyeIris[2][1])):0;h.push({...b,age:A.age,gender:r.gender,genderConfidence:r.confidence,emotion:c,embedding:_,iris:I!==0?Math.trunc(I)/100:0,angle:k,tensor:this.config.face.detector.return?(f=b.image)==null?void 0:f.squeeze():null}),(x=b.image)==null||x.dispose(),u(this,O).call(this,"End Face")}return u(this,O).call(this,"End 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this.detect(c,this.config);e(h)},t?r.src=t:e(null)}));c1.set(this,async()=>{let e=_=>Buffer.from(_,"base64"),t=this.config.warmup==="face"?e(De):e(Ge),A=m0.node.decodeJpeg(t),r=A.expandDims(0);this.tf.dispose(A);let c=await this.detect(r,this.config);return this.tf.dispose(r),c});this.tf=m0,this.draw=l0,Ae(this,e1,y0),this.version=w0,this.config=Te(S,e),this.state="idle",Ae(this,pe,0),Ae(this,Pe,!1),Ae(this,ve,!1),Ae(this,le,!0),Ae(this,P,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=t=>a0(t,this.config),this.classes={facemesh:u0,age:m1,gender:b1,emotion:M1,body:this.config.body.modelPath.includes("posenet")?J1:c0,hand:e0,nanodet:o0},this.sysinfo=z0()}profileData(){return this.config.profile?f1:{}}simmilarity(e,t){return this.config.face.embedding.enabled?W1(e,t):0}enhance(e){return O1(e)}match(e,t,A=0){return F0(e,t,A)}async load(e={}){this.state="load";let t=R();e&&(this.config=Te(this.config,e)),u(this,le)&&(this.config.debug&&g(`version: ${this.version}`),this.config.debug&&g(`tfjs version: ${this.tf.version_core}`),this.config.debug&&g("platform:",this.sysinfo.platform),this.config.debug&&g("agent:",this.sysinfo.agent),await u(this,ze).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&g("configuration:",this.config),this.config.debug&&g("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?u0.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?u1(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?v1(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?N1(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?j1(this.config):null),this.models.handpose||(this.config.hand.enabled?A0(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?U1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?_0(this.config):null),this.models.nanodet||(this.config.object.enabled?i0(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await u0.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await u1(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await v1(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await N1(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await j1(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await A0(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await U1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await _0(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await i0(this.config))),u(this,le)&&(this.config.debug&&g("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),Ae(this,le,!1));let A=Math.trunc(R()-t);A>(u(this,P).load||0)&&(u(this,P).load=A)}async detect(e,t={}){return new Promise(async A=>{var d,f,x,b;this.state="config";let r;this.config=Te(this.config,t),this.state="check";let c=u(this,t1).call(this,e);c&&(g(c,e),A({error:c}));let _=R();await u(this,ze).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),u(this,O).call(this,"Start Scope:"),r=R();let h=a0(e,this.config);if(!h||!h.tensor){g("could not convert input to tensor"),A({error:"could not convert input to tensor"});return}u(this,P).image=Math.trunc(R()-r),u(this,O).call(this,"Get Image:");let o,s,a,i;this.config.async?(a=this.config.face.enabled?u(this,Me).call(this,h.tensor):[],u(this,P).face&&delete u(this,P).face):(this.state="run:face",r=R(),a=this.config.face.enabled?await u(this,Me).call(this,h.tensor):[],u(this,P).face=Math.trunc(R()-r)),u(this,O).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?(d=this.models.posenet)==null?void 0:d.estimatePoses(h.tensor,this.config):[]:o=this.config.body.enabled?h0(h.tensor,this.config):[],u(this,P).body&&delete u(this,P).body):(this.state="run:body",r=R(),this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?await((f=this.models.posenet)==null?void 0:f.estimatePoses(h.tensor,this.config)):[]:o=this.config.body.enabled?await h0(h.tensor,this.config):[],u(this,P).body=Math.trunc(R()-r)),u(this,O).call(this,"End Body:"),u(this,O).call(this,"Start Hand:"),this.config.async?(s=this.config.hand.enabled?(x=this.models.handpose)==null?void 0:x.estimateHands(h.tensor,this.config):[],u(this,P).hand&&delete u(this,P).hand):(this.state="run:hand",r=R(),s=this.config.hand.enabled?await((b=this.models.handpose)==null?void 0:b.estimateHands(h.tensor,this.config)):[],u(this,P).hand=Math.trunc(R()-r)),u(this,O).call(this,"End Hand:"),u(this,O).call(this,"Start Object:"),this.config.async?(i=this.config.object.enabled?x0(h.tensor,this.config):[],u(this,P).object&&delete u(this,P).object):(this.state="run:object",r=R(),i=this.config.object.enabled?await x0(h.tensor,this.config):[],u(this,P).object=Math.trunc(R()-r)),u(this,O).call(this,"End Object:"),this.config.async&&([a,o,s,i]=await Promise.all([a,o,s,i])),h.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),u(this,O).call(this,"End Scope:");let l=[];this.config.gesture.enabled&&(r=R(),l=[...pt(a),...ut(o),...gt(s),...bt(a)],this.config.async?u(this,P).gesture&&delete u(this,P).gesture:u(this,P).gesture=Math.trunc(R()-r)),u(this,P).total=Math.trunc(R()-_),this.state="idle",A({face:a,body:o,hand:s,gesture:l,object:i,performance:u(this,P),canvas:h.canvas})})}async warmup(e={}){let t=R();e&&(this.config=Te(this.config,e));let A=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await u(this,r1).call(this):typeof Image!="undefined"?r=await u(this,A1).call(this):r=await u(this,c1).call(this),this.config.videoOptimized=A;let c=R();return this.config.debug&&g("Warmup",this.config.warmup,Math.round(c-t),"ms",r),r}};e1=new WeakMap,P=new WeakMap,pe=new WeakMap,Pe=new WeakMap,ve=new WeakMap,le=new WeakMap,O=new WeakMap,t1=new WeakMap,ze=new WeakMap,n1=new WeakMap,Me=new WeakMap,r1=new WeakMap,A1=new WeakMap,c1=new WeakMap;0&&(module.exports={Human});
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dt={};U(dt,{all:()=>Kn,body:()=>F0,canvas:()=>Cn,drawOptions:()=>y,face:()=>X0,gesture:()=>H0,hand:()=>q0,object:()=>B0});var y={color:"rgba(173, 216, 230, 0.3)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",font:'small-caps 16px "Segoe UI"',lineHeight:20,lineWidth:6,pointSize:2,roundRect:28,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawPolygons:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,bufferedOutput:!1,useRawBoxes:!1};function $e(n,e,t,A=null){n.fillStyle=y.useDepth&&A?`rgba(${127.5+2*(A||0)}, ${127.5-2*(A||0)}, 255, 0.3)`:y.color,n.beginPath(),n.arc(e,t,y.pointSize,0,2*Math.PI),n.fill()}function pe(n,e,t,A,r){if(n.beginPath(),y.useCurves){let c=(e+e+A)/2,_=(t+t+r)/2;n.ellipse(c,_,A/2,r/2,0,0,2*Math.PI)}else 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0:s.estimateFaces(e,this.config));if(u(this,P).face=Math.trunc(M()-t),!o)return[];for(let b of o){if(u(this,k).call(this,"Get Face"),!b.image||b.image.isDisposedInternal){g("Face object is disposed:",b.image);continue}let j=u(this,r1).call(this,b.mesh);u(this,k).call(this,"Start Age:"),this.config.async?A=this.config.face.age.enabled?b1(b.image,this.config):{}:(this.state="run:age",t=M(),A=this.config.face.age.enabled?await b1(b.image,this.config):{},u(this,P).age=Math.trunc(M()-t)),u(this,k).call(this,"Start Gender:"),this.config.async?r=this.config.face.gender.enabled?R1(b.image,this.config):{}:(this.state="run:gender",t=M(),r=this.config.face.gender.enabled?await R1(b.image,this.config):{},u(this,P).gender=Math.trunc(M()-t)),u(this,k).call(this,"Start Emotion:"),this.config.async?c=this.config.face.emotion.enabled?j1(b.image,this.config):{}:(this.state="run:emotion",t=M(),c=this.config.face.emotion.enabled?await j1(b.image,this.config):{},u(this,P).emotion=Math.trunc(M()-t)),u(this,k).call(this,"End Emotion:"),u(this,k).call(this,"Start Embedding:"),this.config.async?_=this.config.face.embedding.enabled?I1(b,this.config):[]:(this.state="run:embedding",t=M(),_=this.config.face.embedding.enabled?await I1(b,this.config):[],u(this,P).embedding=Math.trunc(M()-t)),u(this,k).call(this,"End Emotion:"),this.config.async&&([A,r,c,_]=await Promise.all([A,r,c,_])),u(this,k).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((a=b==null?void 0:b.annotations)==null?void 0:a.leftEyeIris)&&((i=b==null?void 0:b.annotations)==null?void 0:i.rightEyeIris)&&(delete b.annotations.leftEyeIris,delete b.annotations.rightEyeIris);let I=((l=b.annotations)==null?void 0:l.leftEyeIris)&&((m=b.annotations)==null?void 0:m.rightEyeIris)?11.7*Math.max(Math.abs(b.annotations.leftEyeIris[3][0]-b.annotations.leftEyeIris[1][0]),Math.abs(b.annotations.rightEyeIris[4][1]-b.annotations.rightEyeIris[2][1])):0;h.push({...b,age:A.age,gender:r.gender,genderConfidence:r.confidence,emotion:c,embedding:_,iris:I!==0?Math.trunc(I)/100:0,angle:j,tensor:this.config.face.detector.return?(f=b.image)==null?void 0:f.squeeze():null}),(x=b.image)==null||x.dispose(),u(this,k).call(this,"End Face")}return u(this,k).call(this,"End FaceMesh:"),this.config.async&&(u(this,P).face&&delete u(this,P).face,u(this,P).age&&delete u(this,P).age,u(this,P).gender&&delete u(this,P).gender,u(this,P).emotion&&delete u(this,P).emotion),h});A1.set(this,async()=>{let e=(r,c="application/octet-stream")=>fetch(`data:${c};base64,${r}`).then(_=>_.blob()),t,A;switch(this.config.warmup){case"face":t=await e(Ge);break;case"full":t=await e(Qe);break;default:t=null}if(t){let r=await createImageBitmap(t);A=await this.detect(r,this.config),r.close()}return A});c1.set(this,async()=>new Promise(e=>{let t,A=0;switch(this.config.warmup){case"face":A=256,t="data:image/jpeg;base64,"+Ge;break;case"full":case"body":A=1200,t="data:image/jpeg;base64,"+Qe;break;default:t=null}let r=new Image;r.onload=async()=>{let c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(A,A):document.createElement("canvas");c.width=r.naturalWidth,c.height=r.naturalHeight;let _=c.getContext("2d");_==null||_.drawImage(r,0,0);let h=await this.detect(c,this.config);e(h)},t?r.src=t:e(null)}));_1.set(this,async()=>{let e=_=>Buffer.from(_,"base64"),t=this.config.warmup==="face"?e(Ge):e(Qe),A=mt.node.decodeJpeg(t),r=A.expandDims(0);this.tf.dispose(A);let c=await this.detect(r,this.config);return this.tf.dispose(r),c});this.tf=mt,this.draw=dt,Ae(this,t1,wt),this.version=lt,this.config=Pe(S,e),this.state="idle",Ae(this,be,0),Ae(this,ve,!1),Ae(this,ze,!1),Ae(this,le,!0),Ae(this,P,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=t=>yt(t,this.config),this.classes={facemesh:ut,age:u1,gender:g1,emotion:M1,body:this.config.body.modelPath.includes("posenet")?K1:_t,hand:tt,nanodet:st},this.sysinfo=zt()}profileData(){return this.config.profile?m1:{}}simmilarity(e,t){return this.config.face.embedding.enabled?O1(e,t):0}enhance(e){return k1(e)}match(e,t,A=0){return Ft(e,t,A)}async load(e={}){this.state="load";let t=M();e&&(this.config=Pe(this.config,e)),u(this,le)&&(this.config.debug&&g(`version: ${this.version}`),this.config.debug&&g(`tfjs version: ${this.tf.version_core}`),this.config.debug&&g("platform:",this.sysinfo.platform),this.config.debug&&g("agent:",this.sysinfo.agent),await u(this,Re).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&g("configuration:",this.config),this.config.debug&&g("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?ut.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?p1(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?z1(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?S1(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?W1(this.config):null),this.models.handpose||(this.config.hand.enabled?ct(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?D1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?ht(this.config):null),this.models.nanodet||(this.config.object.enabled?xt(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await ut.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await p1(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await z1(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await S1(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await W1(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await ct(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await D1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await ht(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await xt(this.config))),u(this,le)&&(this.config.debug&&g("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),Ae(this,le,!1));let A=Math.trunc(M()-t);A>(u(this,P).load||0)&&(u(this,P).load=A)}async detect(e,t={}){return new Promise(async A=>{var f,x,b,j;this.state="config";let r;this.config=Pe(this.config,t),this.state="check";let c=u(this,n1).call(this,e);c&&(g(c,e),A({error:c}));let _=M();await u(this,Re).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),u(this,k).call(this,"Start Scope:"),r=M();let h=yt(e,this.config);if(!h||!h.tensor){g("could not convert input to tensor"),A({error:"could not convert input to tensor"});return}u(this,P).image=Math.trunc(M()-r),u(this,k).call(this,"Get Image:");let o,s,a,i;this.config.async?(a=this.config.face.enabled?u(this,Me).call(this,h.tensor):[],u(this,P).face&&delete u(this,P).face):(this.state="run:face",r=M(),a=this.config.face.enabled?await u(this,Me).call(this,h.tensor):[],u(this,P).face=Math.trunc(M()-r)),u(this,k).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?(f=this.models.posenet)==null?void 0:f.estimatePoses(h.tensor,this.config):[]:o=this.config.body.enabled?ot(h.tensor,this.config):[],u(this,P).body&&delete u(this,P).body):(this.state="run:body",r=M(),this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?await((x=this.models.posenet)==null?void 0:x.estimatePoses(h.tensor,this.config)):[]:o=this.config.body.enabled?await ot(h.tensor,this.config):[],u(this,P).body=Math.trunc(M()-r)),u(this,k).call(this,"End Body:"),u(this,k).call(this,"Start Hand:"),this.config.async?(s=this.config.hand.enabled?(b=this.models.handpose)==null?void 0:b.estimateHands(h.tensor,this.config):[],u(this,P).hand&&delete u(this,P).hand):(this.state="run:hand",r=M(),s=this.config.hand.enabled?await((j=this.models.handpose)==null?void 0:j.estimateHands(h.tensor,this.config)):[],u(this,P).hand=Math.trunc(M()-r)),u(this,k).call(this,"End Hand:"),u(this,k).call(this,"Start Object:"),this.config.async?(i=this.config.object.enabled?at(h.tensor,this.config):[],u(this,P).object&&delete u(this,P).object):(this.state="run:object",r=M(),i=this.config.object.enabled?await at(h.tensor,this.config):[],u(this,P).object=Math.trunc(M()-r)),u(this,k).call(this,"End Object:"),this.config.async&&([a,o,s,i]=await Promise.all([a,o,s,i])),h.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),u(this,k).call(this,"End Scope:");let l=[];this.config.gesture.enabled&&(r=M(),l=[...p0(a),...u0(o),...g0(s),...b0(a)],this.config.async?u(this,P).gesture&&delete u(this,P).gesture:u(this,P).gesture=Math.trunc(M()-r)),u(this,P).total=Math.trunc(M()-_),this.state="idle";let m={face:a,body:o,hand:s,gesture:l,object:i,performance:u(this,P),canvas:h.canvas};A(m)})}async warmup(e={}){let t=M();e&&(this.config=Pe(this.config,e));let A=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await u(this,A1).call(this):typeof Image!="undefined"?r=await u(this,c1).call(this):r=await u(this,_1).call(this),this.config.videoOptimized=A;let c=M();return this.config.debug&&g("Warmup",this.config.warmup,Math.round(c-t),"ms",r),r}};t1=new WeakMap,P=new WeakMap,be=new WeakMap,ve=new WeakMap,ze=new WeakMap,le=new WeakMap,k=new WeakMap,n1=new WeakMap,Re=new WeakMap,r1=new WeakMap,Me=new WeakMap,A1=new WeakMap,c1=new WeakMap,_1=new WeakMap;0&&(module.exports={Human});
 //# sourceMappingURL=human.node-gpu.js.map
diff --git a/dist/human.node-gpu.js.map b/dist/human.node-gpu.js.map
index a8a19f13..f58eb463 100644
--- a/dist/human.node-gpu.js.map
+++ b/dist/human.node-gpu.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["../src/tfjs/tf-node-gpu.ts", "../src/blazeface/facemesh.ts", "../src/posenet/keypoints.ts", "../src/human.ts", "../src/log.ts", "../src/sysinfo.ts", "../src/tfjs/backend.ts", "../src/blazeface/blazeface.ts", "../src/blazeface/facepipeline.ts", "../src/blazeface/box.ts", "../src/blazeface/util.ts", "../src/blazeface/coords.ts", "../src/age/age.ts", "../src/profile.ts", "../src/gender/gender.ts", "../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/decodePose.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/handdetector.ts", "../src/handpose/box.ts", "../src/handpose/handpipeline.ts", "../src/handpose/util.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/nanodet/nanodet.ts", "../src/gesture/gesture.ts", "../src/image.ts", "../src/imagefx.js", "../config.ts", "../src/sample.ts", "../src/draw.ts"],
-  "sourcesContent": ["export * from '@tensorflow/tfjs-node-gpu';\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - prediction.box.startPoint[0],\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - prediction.box.startPoint[1],\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0] / input.shape[2]),\n        Math.max(0, prediction.box.startPoint[1] / input.shape[1]),\n        Math.min(input.shape[1], (prediction.box.endPoint[0]) - prediction.box.startPoint[0]) / input.shape[2],\n        Math.min(input.shape[2], (prediction.box.endPoint[1]) - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        mesh,\n        boxRaw,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      resolve({ face: faceRes, body: bodyRes, hand: handRes, gesture: gestureRes, object: objectRes, performance: this.#perf, canvas: process.canvas });\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 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0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - prediction.box.topLeft[0],\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - prediction.box.topLeft[1],\n      ] : 0;\n      hands.push({ confidence: prediction.confidence, box, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            boxRaw[0] * outputShape[0],\n            boxRaw[1] * outputShape[1],\n            boxRaw[2] * outputShape[0],\n            boxRaw[3] * outputShape[1],\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n      // rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2] - h.box[0], h.box[3] - h.box[1]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
-  "mappings": 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+  "sourcesContent": ["export * from '@tensorflow/tfjs-node-gpu';\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    boxRaw: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.#perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 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0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: prediction.confidence, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            Math.max(0, (boxRaw[0] * outputShape[0])),\n            Math.max(0, (boxRaw[1] * outputShape[1])),\n            Math.min(1, (boxRaw[2] * outputShape[0]) - (boxRaw[0] * outputShape[0])),\n            Math.min(1, (boxRaw[3] * outputShape[1]) - (boxRaw[1] * outputShape[1])),\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
+  "mappings": 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   "names": []
 }
diff --git a/dist/human.node.js b/dist/human.node.js
index 3a18d84d..730aac9a 100644
--- a/dist/human.node.js
+++ b/dist/human.node.js
@@ -5,14 +5,14 @@
   author: <https://github.com/vladmandic>'
   */
 
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ln=[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],dn=[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],fn=[33,133,362,263,1,78,308],hr=ln.map(n=>x1[n]),or=dn.map(n=>x1[n]),sr=fn.map(n=>x1[n]);var a1=te.leftEyeLower0,y1=te.rightEyeLower0,me={leftBounds:[a1[0],a1[a1.length-1]],rightBounds:[y1[0],y1[y1.length-1]]},Oe={count:468,mouth:13,symmetryLine:[13,te.midwayBetweenEyes[0]]},L0={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},ue={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function ke(n,e,t,A){for(let r=0;r<i1.length;r++){let{key:c,indices:_}=i1[r],h=te[`${t}${c}`];if(!A||A.includes(c))for(let o=0;o<_.length;o++){let s=_[o];n[h[o]]=[e[s][0],e[s][1],(e[s][2]+n[h[o]][2])/2]}}}var w1=class{constructor(e,t,A){var r,c;this.storedBoxes=[],this.boundingBoxDetector=e,this.meshDetector=t,this.irisModel=A,this.boxSize=((r=e==null?void 0:e.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(t==null?void 0:t.inputs[0].shape[2])||((c=e==null?void 0:e.model)==null?void 0:c.inputs[0].shape[2]),this.irisSize=(A==null?void 0:A.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,t,A,r){let c=be({startPoint:t.startPoint,endPoint:t.endPoint}),_=e.map(i=>[c[0]/this.meshSize*(i[0]-this.meshSize/2),c[1]/this.meshSize*(i[1]-this.meshSize/2),i[2]]),h=A!==0?We(A,[0,0]):je,o=A!==0?_.map(i=>[...V0(i,h),i[2]]):_,s=A!==0?Z0(r):je,a=[...de({startPoint:t.startPoint,endPoint:t.endPoint}),1];return o.map(i=>[i[0]+he(a,s[0]),i[1]+he(a,s[1]),i[2]])}getLeftToRightEyeDepthDifference(e){let t=e[me.leftBounds[0]][2],A=e[me.rightBounds[0]][2];return t-A}getEyeBox(e,t,A,r,c=!1){let _=Se(Ne(this.calculateLandmarksBoundingBox([e[A],e[r]]),this.irisEnlarge)),h=be(_),o=q.image.cropAndResize(t,[[_.startPoint[1]/this.meshSize,_.startPoint[0]/this.meshSize,_.endPoint[1]/this.meshSize,_.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return c&&q.ENV.flags.IS_BROWSER&&(o=q.image.flipLeftRight(o)),{box:_,boxSize:h,crop:o}}getEyeCoords(e,t,A,r=!1){let c=[];for(let _=0;_<ue.numCoordinates;_++){let h=e[_*3],o=e[_*3+1],s=e[_*3+2];c.push([(r?1-h/this.irisSize:h/this.irisSize)*A[0]+t.startPoint[0],o/this.irisSize*A[1]+t.startPoint[1],s])}return{rawCoords:c,iris:c.slice(ue.index)}}getAdjustedIrisCoords(e,t,A){let r=e[te[`${A}EyeUpper0`][ue.upperCenter]][2],c=e[te[`${A}EyeLower0`][ue.lowerCenter]][2],_=(r+c)/2;return t.map((h,o)=>{let s=_;return o===2?s=r:o===4&&(s=c),[h[0],h[1],s]})}async predict(e,t){let A=!1,r;if((this.skipped===0||this.skipped>t.face.detector.skipFrames||!t.face.mesh.enabled||!t.videoOptimized)&&(r=await this.boundingBoxDetector.getBoundingBoxes(e),this.skipped=0),t.videoOptimized&&this.skipped++,r&&r.boxes&&(!t.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==t.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let _ of r.boxes)this.storedBoxes.push({startPoint:_.box.startPoint.dataSync(),endPoint:_.box.endPoint.dataSync(),landmarks:_.landmarks,confidence:_.confidence});this.storedBoxes.length>0&&(A=!0)}if(t.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),A){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let _=0;_<this.storedBoxes.length;_++){let h=O0({startPoint:this.storedBoxes[_].startPoint,endPoint:this.storedBoxes[_].endPoint},r.scaleFactor),o=Ne(h),s=Se(o),a=this.storedBoxes[_].landmarks.arraySync(),i=this.storedBoxes[_].confidence;this.storedBoxes[_]={...s,confidence:i,landmarks:a}}}r&&r.boxes&&r.boxes.forEach(_=>{_.box.startPoint.dispose(),_.box.endPoint.dispose(),_.landmarks.dispose()});let c=q.tidy(()=>this.storedBoxes.map((_,h)=>{let o=_.confidence,s,a=0,i;if(t.face.detector.rotation&&t.face.mesh.enabled&&q.ENV.flags.IS_BROWSER){let[p,y]=_.landmarks.length>=Oe.count?Oe.symmetryLine:L0.symmetryLine;a=s1(_.landmarks[p],_.landmarks[y]);let m=de({startPoint:_.startPoint,endPoint:_.endPoint}),z=[m[0]/e.shape[2],m[1]/e.shape[1]],E=q.image.rotateWithOffset(e,a,0,z);i=We(-a,m),t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{i=je;let p=e.clone();t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},p,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},p,[this.boxSize,this.boxSize]).div(255)}if(!t.face.mesh.enabled)return{coords:null,box:_,faceConfidence:null,boxConfidence:_.confidence,confidence:_.confidence,image:s};let[,l,d]=this.meshDetector.predict(s),f=l.dataSync()[0];if(f<t.face.detector.minConfidence)return null;let b=q.reshape(d,[-1,3]).arraySync();if(t.face.iris.enabled){let{box:p,boxSize:y,crop:m}=this.getEyeBox(b,s,me.leftBounds[0],me.leftBounds[1],!0),{box:z,boxSize:E,crop:L}=this.getEyeBox(b,s,me.rightBounds[0],me.rightBounds[1]),b0=this.irisModel.predict(q.concat([m,L])).dataSync(),Yt=b0.slice(0,ue.numCoordinates*3),{rawCoords:g0,iris:Bt}=this.getEyeCoords(Yt,p,y,!0),Jt=b0.slice(ue.numCoordinates*3),{rawCoords:T0,iris:Kt}=this.getEyeCoords(Jt,z,E),P0=this.getLeftToRightEyeDepthDifference(b);Math.abs(P0)<30?(ke(b,g0,"left",null),ke(b,T0,"right",null)):P0<1?ke(b,g0,"left",["EyeUpper0","EyeLower0"]):ke(b,T0,"right",["EyeUpper0","EyeLower0"]);let Ut=this.getAdjustedIrisCoords(b,Bt,"left"),Dt=this.getAdjustedIrisCoords(b,Kt,"right");b=b.concat(Ut).concat(Dt)}let k=this.transformRawCoords(b,_,a,i);_=Ne(this.calculateLandmarksBoundingBox(k),1.5);let I=q.tensor2d(k);if(t.face.detector.rotation&&t.face.mesh.enabled&&t.face.detector.return&&q.ENV.flags.IS_BROWSER){let[p,y]=_.landmarks.length>=Oe.count?Oe.symmetryLine:L0.symmetryLine;a=s1(_.landmarks[p],_.landmarks[y]);let m=de({startPoint:_.startPoint,endPoint:_.endPoint}),z=[m[0]/e.shape[2],m[1]/e.shape[1]],E=q.image.rotateWithOffset(e,a,0,z);i=We(-a,m),s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let M={coords:I,box:_,faceConfidence:f,boxConfidence:o,image:s,rawCoords:b},B=Se(_);return this.storedBoxes[h]={...B,landmarks:k,confidence:_.confidence,faceConfidence:f},M}));return c=c.filter(_=>_!==null),t.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(_=>_.faceConfidence>t.face.detector.minConfidence)),this.detectedFaces=c.length,c}calculateLandmarksBoundingBox(e){let t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c,landmarks:e}}};var u0=j(X0());var m1={};U(m1,{load:()=>u1,predict:()=>p1});var ne=j(Z());var f1={};function D(n,e){if(!e||!e.kernels)return;let t=5,A=e.kernels.filter(h=>h.kernelTimeMs>0).reduce((h,o)=>h+=o.kernelTimeMs,0),r=e.kernels.map((h,o)=>(h.id=o,h)).filter(h=>h.kernelTimeMs>0).sort((h,o)=>o.kernelTimeMs-h.kernelTimeMs),c=e.kernels.map((h,o)=>(h.id=o,h)).filter(h=>h.totalBytesSnapshot>0).sort((h,o)=>o.totalBytesSnapshot-h.totalBytesSnapshot);r.length>t&&(r.length=t),c.length>t&&(c.length=t);let _={newBytes:e.newBytes,newTensors:e.newTensors,peakBytes:e.peakBytes,numKernelOps:e.kernels.length,timeKernelOps:A,slowestKernelOps:r,largestKernelOps:c};f1[n]=_,g("Human profiler",n,_)}var oe,Ie={age:0},Ze=Number.MAX_SAFE_INTEGER;async function u1(n){return oe||(oe=await ne.loadGraphModel(n.face.age.modelPath),n.debug&&g(`load model: ${n.face.age.modelPath.match(/\/(.*)\./)[1]}`)),oe}async function p1(n,e){return 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ce?Ve<e.face.gender.skipFrames&&e.videoOptimized&&g1.gender!==""?(Ve++,g1):(e.videoOptimized?Ve=0:Ve=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=H.image.resizeBilinear(n,[ce.inputs[0].shape[2],ce.inputs[0].shape[1]],!1),r;T1?r=H.tidy(()=>{let[h,o,s]=H.split(A,3,3),a=H.mul(h,P1[0]),i=H.mul(o,P1[1]),l=H.mul(s,P1[2]);return H.addN([a,i,l]).sub(.5).mul(2)}):r=H.mul(A,[255]),H.dispose(A);let c,_={gender:"",confidence:0};if(!e.profile)e.face.gender.enabled&&(c=await ce.predict(r));else{let h=e.face.gender.enabled?await H.profile(()=>ce.predict(r)):{};c=h.result.clone(),h.result.dispose(),D("gender",h)}if(r.dispose(),c){let h=c.dataSync();if(T1)(h[0]>e.face.gender.minConfidence||h[1]>e.face.gender.minConfidence)&&(_.gender=h[0]>h[1]?"female":"male",_.confidence=h[0]>h[1]?Math.trunc(100*h[0])/100:Math.trunc(100*h[1])/100);else{let o=Math.trunc(200*Math.abs(h[0]-.5))/100;o>e.face.gender.minConfidence&&(_.gender=h[0]<=.5?"female":"male",_.confidence=Math.min(.99,o))}}c.dispose(),g1=_,t(_)})):null}var M1={};U(M1,{load:()=>N1,predict:()=>S1});var X=j(Z());var un=["angry","disgust","fear","happy","sad","surprise","neutral"],se,R1=[],Le=Number.MAX_SAFE_INTEGER,E1=[.2989,.587,.114];async function N1(n){return se||(se=await X.loadGraphModel(n.face.emotion.modelPath),n.debug&&g(`load model: ${n.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),se}async function S1(n,e){return se?Le<e.face.emotion.skipFrames&&e.videoOptimized&&R1.length>0?(Le++,R1):(e.videoOptimized?Le=0:Le=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=X.image.resizeBilinear(n,[se.inputs[0].shape[2],se.inputs[0].shape[1]],!1),[r,c,_]=X.split(A,3,3);A.dispose();let h=X.mul(r,E1[0]),o=X.mul(c,E1[1]),s=X.mul(_,E1[2]);r.dispose(),c.dispose(),_.dispose();let a=X.addN([h,o,s]);h.dispose(),o.dispose(),s.dispose();let i=X.tidy(()=>a.sub(.5).mul(2));a.dispose();let l=[];if(e.face.emotion.enabled){let d;if(e.profile){let f=await X.profile(()=>se.predict(i));d=f.result.dataSync(),f.result.dispose(),D("emotion",f)}else{let f=await se.predict(i);d=f.dataSync(),X.dispose(f)}for(let f=0;f<d.length;f++)d[f]>e.face.emotion.minConfidence&&l.push({score:Math.min(.99,Math.trunc(100*d[f])/100),emotion:un[f]});l.sort((f,x)=>x.score-f.score)}i.dispose(),R1=l,t(l)})):null}var N=j(Z());var re;async function j1(n){return re||(re=await N.loadGraphModel(n.face.embedding.modelPath),n.debug&&g(`load model: ${n.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),re}function W1(n,e,t=2){if(!n||!e||(n==null?void 0:n.length)===0||(e==null?void 0:e.length)===0||(n==null?void 0:n.length)!==(e==null?void 0:e.length))return 0;let A=n.map((c,_)=>Math.abs(n[_]-e[_])**t).reduce((c,_)=>c+_,0)**(1/t);return Math.max(Math.trunc(1e3*(1-A))/1e3,0)}function F0(n,e,t=0){let A={simmilarity:0,name:"",source:"",embedding:[]};if(!n||!e||!Array.isArray(n)||!Array.isArray(e))return A;for(let r of e)if(r.embedding&&r.name){let c=W1(n,r.embedding);c>t&&c>A.simmilarity&&(A={...r,simmilarity:c})}return A}function O1(n){return N.tidy(()=>{let t=[[.05,.15,.85,.85]],A=n.image||n.tensor;if(!(A instanceof N.Tensor))return null;let r=A.shape.length===3?N.image.cropAndResize(N.expandDims(A,0),t,[0],[re.inputs[0].shape[2],re.inputs[0].shape[1]]):N.image.cropAndResize(A,t,[0],[re.inputs[0].shape[2],re.inputs[0].shape[1]]),c=[.2989,.587,.114],[_,h,o]=N.split(r,3,3),s=N.mul(_,c[0]),a=N.mul(h,c[1]),i=N.mul(o,c[2]),l=N.addN([s,a,i]),d=N.stack([l,l,l],3).squeeze(4),f=d.sub(d.min());return f.div(f.max())})}async function k1(n,e){return re?new Promise(async t=>{let A=[];if(e.face.embedding.enabled){let r=O1(n);if(!e.profile)A=N.tidy(()=>[...re.predict(r).reshape([128,2]).logSumExp(1).dataSync()]);else{let c=await 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t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c}}};var dt=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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ft=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],mt=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var G;async function _0(n){return G||(G=await xe.loadGraphModel(n.body.modelPath),G.width=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[2].size),G.height=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[1].size),n.debug&&g(`load model: ${n.body.modelPath.match(/\/(.*)\./)[1]}`)),G}async function h0(n,e){if(!G||!e.body.enabled)return null;let t={width:n.shape[2],height:n.shape[1]},A=xe.image.resizeBilinear(n,[G.width,G.height],!1),r=xe.div(A,[255]);A.dispose();let c;if(e.profile){let s=await xe.profile(()=>G.predict(r));c=s.result.find(a=>a.size===195||a.size===155).dataSync(),s.result.forEach(a=>a.dispose()),D("blazepose",s)}else{let s=await G.predict(r);c=s.find(a=>a.size===195||a.size===155).dataSync(),s.forEach(a=>a.dispose())}r.dispose();let _=[],h=c.length===195?ft:mt,o=5;for(let 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ln=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],dn=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],fn=[33,133,362,263,1,78,308],hr=ln.map(n=>a1[n]),or=dn.map(n=>a1[n]),sr=fn.map(n=>a1[n]);var y1=te.leftEyeLower0,w1=te.rightEyeLower0,me={leftBounds:[y1[0],y1[y1.length-1]],rightBounds:[w1[0],w1[w1.length-1]]},ke={count:468,mouth:13,symmetryLine:[13,te.midwayBetweenEyes[0]]},Vt={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},ue={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function Ie(n,e,t,A){for(let r=0;r<x1.length;r++){let{key:c,indices:_}=x1[r],h=te[`${t}${c}`];if(!A||A.includes(c))for(let o=0;o<_.length;o++){let s=_[o];n[h[o]]=[e[s][0],e[s][1],(e[s][2]+n[h[o]][2])/2]}}}var l1=class{constructor(e,t,A){var r,c;this.storedBoxes=[],this.boundingBoxDetector=e,this.meshDetector=t,this.irisModel=A,this.boxSize=((r=e==null?void 0:e.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(t==null?void 0:t.inputs[0].shape[2])||((c=e==null?void 0:e.model)==null?void 0:c.inputs[0].shape[2]),this.irisSize=(A==null?void 0:A.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(e,t,A,r){let c=ge({startPoint:t.startPoint,endPoint:t.endPoint}),_=e.map(i=>[c[0]/this.meshSize*(i[0]-this.meshSize/2),c[1]/this.meshSize*(i[1]-this.meshSize/2),i[2]]),h=A!==0?Oe(A,[0,0]):We,o=A!==0?_.map(i=>[...Lt(i,h),i[2]]):_,s=A!==0?Zt(r):We,a=[...de({startPoint:t.startPoint,endPoint:t.endPoint}),1];return o.map(i=>[i[0]+he(a,s[0]),i[1]+he(a,s[1]),i[2]])}getLeftToRightEyeDepthDifference(e){let t=e[me.leftBounds[0]][2],A=e[me.rightBounds[0]][2];return t-A}getEyeBox(e,t,A,r,c=!1){let _=je(Se(this.calculateLandmarksBoundingBox([e[A],e[r]]),this.irisEnlarge)),h=ge(_),o=q.image.cropAndResize(t,[[_.startPoint[1]/this.meshSize,_.startPoint[0]/this.meshSize,_.endPoint[1]/this.meshSize,_.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return c&&q.ENV.flags.IS_BROWSER&&(o=q.image.flipLeftRight(o)),{box:_,boxSize:h,crop:o}}getEyeCoords(e,t,A,r=!1){let c=[];for(let _=0;_<ue.numCoordinates;_++){let h=e[_*3],o=e[_*3+1],s=e[_*3+2];c.push([(r?1-h/this.irisSize:h/this.irisSize)*A[0]+t.startPoint[0],o/this.irisSize*A[1]+t.startPoint[1],s])}return{rawCoords:c,iris:c.slice(ue.index)}}getAdjustedIrisCoords(e,t,A){let r=e[te[`${A}EyeUpper0`][ue.upperCenter]][2],c=e[te[`${A}EyeLower0`][ue.lowerCenter]][2],_=(r+c)/2;return t.map((h,o)=>{let s=_;return o===2?s=r:o===4&&(s=c),[h[0],h[1],s]})}async predict(e,t){let A=!1,r;if((this.skipped===0||this.skipped>t.face.detector.skipFrames||!t.face.mesh.enabled||!t.videoOptimized)&&(r=await this.boundingBoxDetector.getBoundingBoxes(e),this.skipped=0),t.videoOptimized&&this.skipped++,r&&r.boxes&&(!t.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==t.face.detector.maxFaces)){this.storedBoxes=[],this.detectedFaces=0;for(let _ of r.boxes)this.storedBoxes.push({startPoint:_.box.startPoint.dataSync(),endPoint:_.box.endPoint.dataSync(),landmarks:_.landmarks,confidence:_.confidence});this.storedBoxes.length>0&&(A=!0)}if(t.face.detector.skipInitial&&this.detectedFaces===0&&(this.skipped=0),A){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let _=0;_<this.storedBoxes.length;_++){let h=Ot({startPoint:this.storedBoxes[_].startPoint,endPoint:this.storedBoxes[_].endPoint},r.scaleFactor),o=Se(h),s=je(o),a=this.storedBoxes[_].landmarks.arraySync(),i=this.storedBoxes[_].confidence;this.storedBoxes[_]={...s,confidence:i,landmarks:a}}}r&&r.boxes&&r.boxes.forEach(_=>{_.box.startPoint.dispose(),_.box.endPoint.dispose(),_.landmarks.dispose()});let c=q.tidy(()=>this.storedBoxes.map((_,h)=>{let o=_.confidence,s,a=0,i;if(t.face.detector.rotation&&t.face.mesh.enabled&&q.ENV.flags.IS_BROWSER){let[p,w]=_.landmarks.length>=ke.count?ke.symmetryLine:Vt.symmetryLine;a=i1(_.landmarks[p],_.landmarks[w]);let d=de({startPoint:_.startPoint,endPoint:_.endPoint}),z=[d[0]/e.shape[2],d[1]/e.shape[1]],E=q.image.rotateWithOffset(e,a,0,z);i=Oe(-a,d),t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.boxSize,this.boxSize]).div(255)}else{i=We;let p=e.clone();t.face.mesh.enabled?s=fe({startPoint:_.startPoint,endPoint:_.endPoint},p,[this.meshSize,this.meshSize]).div(255):s=fe({startPoint:_.startPoint,endPoint:_.endPoint},p,[this.boxSize,this.boxSize]).div(255)}if(!t.face.mesh.enabled)return{coords:null,box:_,faceConfidence:null,boxConfidence:_.confidence,confidence:_.confidence,image:s};let[,l,m]=this.meshDetector.predict(s),f=l.dataSync()[0];if(f<t.face.detector.minConfidence)return null;let b=q.reshape(m,[-1,3]).arraySync();if(t.face.iris.enabled){let{box:p,boxSize:w,crop:d}=this.getEyeBox(b,s,me.leftBounds[0],me.leftBounds[1],!0),{box:z,boxSize:E,crop:V}=this.getEyeBox(b,s,me.rightBounds[0],me.rightBounds[1]),bt=this.irisModel.predict(q.concat([d,V])).dataSync(),Y0=bt.slice(0,ue.numCoordinates*3),{rawCoords:gt,iris:J0}=this.getEyeCoords(Y0,p,w,!0),C0=bt.slice(ue.numCoordinates*3),{rawCoords:Tt,iris:K0}=this.getEyeCoords(C0,z,E),Pt=this.getLeftToRightEyeDepthDifference(b);Math.abs(Pt)<30?(Ie(b,gt,"left",null),Ie(b,Tt,"right",null)):Pt<1?Ie(b,gt,"left",["EyeUpper0","EyeLower0"]):Ie(b,Tt,"right",["EyeUpper0","EyeLower0"]);let U0=this.getAdjustedIrisCoords(b,J0,"left"),D0=this.getAdjustedIrisCoords(b,K0,"right");b=b.concat(U0).concat(D0)}let j=this.transformRawCoords(b,_,a,i);_=Se(this.calculateLandmarksBoundingBox(j),1.5);let I=q.tensor2d(j);if(t.face.detector.rotation&&t.face.mesh.enabled&&t.face.detector.return&&q.ENV.flags.IS_BROWSER){let[p,w]=_.landmarks.length>=ke.count?ke.symmetryLine:Vt.symmetryLine;a=i1(_.landmarks[p],_.landmarks[w]);let d=de({startPoint:_.startPoint,endPoint:_.endPoint}),z=[d[0]/e.shape[2],d[1]/e.shape[1]],E=q.image.rotateWithOffset(e,a,0,z);i=Oe(-a,d),s=fe({startPoint:_.startPoint,endPoint:_.endPoint},E,[this.meshSize,this.meshSize]).div(255)}let R={coords:I,box:_,faceConfidence:f,boxConfidence:o,image:s,rawCoords:b},J=je(_);return this.storedBoxes[h]={...J,landmarks:j,confidence:_.confidence,faceConfidence:f},R}));return c=c.filter(_=>_!==null),t.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(_=>_.faceConfidence>t.face.detector.minConfidence)),this.detectedFaces=c.length,c}calculateLandmarksBoundingBox(e){let t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c,landmarks:e}}};var ut=W(Xt());var u1={};U(u1,{load:()=>p1,predict:()=>b1});var ne=W(Z());var m1={};function D(n,e){if(!e||!e.kernels)return;let t=5,A=e.kernels.filter(h=>h.kernelTimeMs>0).reduce((h,o)=>h+=o.kernelTimeMs,0),r=e.kernels.map((h,o)=>(h.id=o,h)).filter(h=>h.kernelTimeMs>0).sort((h,o)=>o.kernelTimeMs-h.kernelTimeMs),c=e.kernels.map((h,o)=>(h.id=o,h)).filter(h=>h.totalBytesSnapshot>0).sort((h,o)=>o.totalBytesSnapshot-h.totalBytesSnapshot);r.length>t&&(r.length=t),c.length>t&&(c.length=t);let _={newBytes:e.newBytes,newTensors:e.newTensors,peakBytes:e.peakBytes,numKernelOps:e.kernels.length,timeKernelOps:A,slowestKernelOps:r,largestKernelOps:c};m1[n]=_,g("Human profiler",n,_)}var oe,Ze={age:0},Le=Number.MAX_SAFE_INTEGER;async function p1(n){return oe||(oe=await ne.loadGraphModel(n.face.age.modelPath),n.debug&&g(`load model: ${n.face.age.modelPath.match(/\/(.*)\./)[1]}`)),oe}async function b1(n,e){return oe?Le<e.face.age.skipFrames&&e.videoOptimized&&Ze.age&&Ze.age>0?(Le++,Ze):(e.videoOptimized?Le=0:Le=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=ne.image.resizeBilinear(n,[oe.inputs[0].shape[2],oe.inputs[0].shape[1]],!1),r=ne.mul(A,[255]);ne.dispose(A);let c,_={age:0};if(!e.profile)e.face.age.enabled&&(c=await oe.predict(r));else{let h=e.face.age.enabled?await ne.profile(()=>oe.predict(r)):{};c=h.result.clone(),h.result.dispose(),D("age",h)}if(r.dispose(),c){let h=c.dataSync();_.age=Math.trunc(10*h[0])/10}c.dispose(),Ze=_,t(_)})):null}var g1={};U(g1,{load:()=>z1,predict:()=>R1});var H=W(Z());var ce,T1={gender:""},Ve=Number.MAX_SAFE_INTEGER,P1=!1,v1=[.2989,.587,.114];async function z1(n){return ce||(ce=await H.loadGraphModel(n.face.gender.modelPath),P1=ce.inputs[0].shape[3]===1,n.debug&&g(`load model: ${n.face.gender.modelPath.match(/\/(.*)\./)[1]}`)),ce}async function R1(n,e){return ce?Ve<e.face.gender.skipFrames&&e.videoOptimized&&T1.gender!==""?(Ve++,T1):(e.videoOptimized?Ve=0:Ve=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=H.image.resizeBilinear(n,[ce.inputs[0].shape[2],ce.inputs[0].shape[1]],!1),r;P1?r=H.tidy(()=>{let[h,o,s]=H.split(A,3,3),a=H.mul(h,v1[0]),i=H.mul(o,v1[1]),l=H.mul(s,v1[2]);return H.addN([a,i,l]).sub(.5).mul(2)}):r=H.mul(A,[255]),H.dispose(A);let c,_={gender:"",confidence:0};if(!e.profile)e.face.gender.enabled&&(c=await ce.predict(r));else{let h=e.face.gender.enabled?await H.profile(()=>ce.predict(r)):{};c=h.result.clone(),h.result.dispose(),D("gender",h)}if(r.dispose(),c){let h=c.dataSync();if(P1)(h[0]>e.face.gender.minConfidence||h[1]>e.face.gender.minConfidence)&&(_.gender=h[0]>h[1]?"female":"male",_.confidence=h[0]>h[1]?Math.trunc(100*h[0])/100:Math.trunc(100*h[1])/100);else{let o=Math.trunc(200*Math.abs(h[0]-.5))/100;o>e.face.gender.minConfidence&&(_.gender=h[0]<=.5?"female":"male",_.confidence=Math.min(.99,o))}}c.dispose(),T1=_,t(_)})):null}var M1={};U(M1,{load:()=>S1,predict:()=>j1});var X=W(Z());var un=["angry","disgust","fear","happy","sad","surprise","neutral"],se,E1=[],He=Number.MAX_SAFE_INTEGER,N1=[.2989,.587,.114];async function S1(n){return se||(se=await X.loadGraphModel(n.face.emotion.modelPath),n.debug&&g(`load model: ${n.face.emotion.modelPath.match(/\/(.*)\./)[1]}`)),se}async function j1(n,e){return se?He<e.face.emotion.skipFrames&&e.videoOptimized&&E1.length>0?(He++,E1):(e.videoOptimized?He=0:He=Number.MAX_SAFE_INTEGER,new Promise(async t=>{let A=X.image.resizeBilinear(n,[se.inputs[0].shape[2],se.inputs[0].shape[1]],!1),[r,c,_]=X.split(A,3,3);A.dispose();let h=X.mul(r,N1[0]),o=X.mul(c,N1[1]),s=X.mul(_,N1[2]);r.dispose(),c.dispose(),_.dispose();let a=X.addN([h,o,s]);h.dispose(),o.dispose(),s.dispose();let i=X.tidy(()=>a.sub(.5).mul(2));a.dispose();let l=[];if(e.face.emotion.enabled){let m;if(e.profile){let f=await X.profile(()=>se.predict(i));m=f.result.dataSync(),f.result.dispose(),D("emotion",f)}else{let f=await se.predict(i);m=f.dataSync(),X.dispose(f)}for(let f=0;f<m.length;f++)m[f]>e.face.emotion.minConfidence&&l.push({score:Math.min(.99,Math.trunc(100*m[f])/100),emotion:un[f]});l.sort((f,x)=>x.score-f.score)}i.dispose(),E1=l,t(l)})):null}var N=W(Z());var re;async function W1(n){return re||(re=await N.loadGraphModel(n.face.embedding.modelPath),n.debug&&g(`load model: ${n.face.embedding.modelPath.match(/\/(.*)\./)[1]}`)),re}function O1(n,e,t=2){if(!n||!e||(n==null?void 0:n.length)===0||(e==null?void 0:e.length)===0||(n==null?void 0:n.length)!==(e==null?void 0:e.length))return 0;let A=n.map((c,_)=>Math.abs(n[_]-e[_])**t).reduce((c,_)=>c+_,0)**(1/t);return Math.max(Math.trunc(1e3*(1-A))/1e3,0)}function Ft(n,e,t=0){let A={simmilarity:0,name:"",source:"",embedding:[]};if(!n||!e||!Array.isArray(n)||!Array.isArray(e))return A;for(let r of e)if(r.embedding&&r.name){let c=O1(n,r.embedding);c>t&&c>A.simmilarity&&(A={...r,simmilarity:c})}return A}function k1(n){return N.tidy(()=>{let t=[[.05,.15,.85,.85]],A=n.image||n.tensor;if(!(A instanceof N.Tensor))return null;let r=A.shape.length===3?N.image.cropAndResize(N.expandDims(A,0),t,[0],[re.inputs[0].shape[2],re.inputs[0].shape[1]]):N.image.cropAndResize(A,t,[0],[re.inputs[0].shape[2],re.inputs[0].shape[1]]),c=[.2989,.587,.114],[_,h,o]=N.split(r,3,3),s=N.mul(_,c[0]),a=N.mul(h,c[1]),i=N.mul(o,c[2]),l=N.addN([s,a,i]),m=N.stack([l,l,l],3).squeeze(4),f=m.sub(m.min());return f.div(f.max())})}async function I1(n,e){return re?new Promise(async t=>{let A=[];if(e.face.embedding.enabled){let r=k1(n);if(!e.profile)A=N.tidy(()=>[...re.predict(r).reshape([128,2]).logSumExp(1).dataSync()]);else{let c=await 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t=e.map(_=>_[0]),A=e.map(_=>_[1]),r=[Math.min(...t),Math.min(...A)],c=[Math.max(...t),Math.max(...A)];return{startPoint:r,endPoint:c}}};var d0=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.734375,y_center:.046875},{w:1,h:1,x_center:.765625,y_center:.046875},{w:1,h:1,x_center:.76562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f0=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPalm","rightPalm","leftIndex","rightIndex","leftPinky","rightPinky","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","midHip","forehead","leftThumb","leftHand","rightThumb","rightHand"],m0=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","left:15","right:16","left:17","right:18","left:19","right:20","left:21","right:22","leftChest","rightChest","neck","forehead","left:27","right:28","left:29","right:30"];var G;async function ht(n){return G||(G=await xe.loadGraphModel(n.body.modelPath),G.width=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[2].size),G.height=parseInt(G.signature.inputs["input_1:0"].tensorShape.dim[1].size),n.debug&&g(`load model: ${n.body.modelPath.match(/\/(.*)\./)[1]}`)),G}async function ot(n,e){if(!G||!e.body.enabled)return null;let t={width:n.shape[2],height:n.shape[1]},A=xe.image.resizeBilinear(n,[G.width,G.height],!1),r=xe.div(A,[255]);A.dispose();let c;if(e.profile){let s=await xe.profile(()=>G.predict(r));c=s.result.find(a=>a.size===195||a.size===155).dataSync(),s.result.forEach(a=>a.dispose()),D("blazepose",s)}else{let s=await G.predict(r);c=s.find(a=>a.size===195||a.size===155).dataSync(),s.forEach(a=>a.dispose())}r.dispose();let _=[],h=c.length===195?f0:m0,o=5;for(let 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r,c=[];c.length=0,r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightHip"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftHip"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),c.length===5&&f0(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="leftHip"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftKnee"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftAnkle"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftHeel"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftFoot"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),$e(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="rightHip"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightKnee"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightAnkle"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightHeel"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightFoot"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),$e(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="leftShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftElbow"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftWrist"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="leftPalm"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),$e(t,c),c.length=0,r=e[A].keypoints.find(_=>_.part==="rightShoulder"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightElbow"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightWrist"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),r=e[A].keypoints.find(_=>_.part==="rightPalm"),r&&r.score>S.body.scoreThreshold&&c.push([r.position.x,r.position.y]),$e(t,c)}}}}async function qt(n,e){if(!e||!n||!(n instanceof HTMLCanvasElement))return;let t=n.getContext("2d");if(!!t){t.lineJoin="round",t.font=w.font;for(let A of e){if(w.drawBoxes&&(t.strokeStyle=w.color,t.fillStyle=w.color,d0(t,A.box[0],A.box[1],A.box[2],A.box[3]),w.drawLabels&&(w.shadowColor&&w.shadowColor!==""&&(t.fillStyle=w.shadowColor,t.fillText("hand",A.box[0]+3,1+A.box[1]+w.lineHeight,A.box[2])),t.fillStyle=w.labelColor,t.fillText("hand",A.box[0]+2,0+A.box[1]+w.lineHeight,A.box[2])),t.stroke()),w.drawPoints&&A.landmarks&&A.landmarks.length>0)for(let r of A.landmarks)t.fillStyle=w.useDepth?`rgba(${127.5+2*r[2]}, ${127.5-2*r[2]}, 255, 0.5)`:w.color,Qe(t,r[0],r[1]);if(w.drawPolygons){let r=c=>{if(!!c)for(let _=0;_<c.length;_++)t.lineWidth=w.lineWidth,t.beginPath(),t.strokeStyle=w.useDepth?`rgba(${127.5+2*c[_][2]}, ${127.5-2*c[_][2]}, 255, 0.5)`:w.color,t.moveTo(c[_>0?_-1:0][0],c[_>0?_-1:0][1]),t.lineTo(c[_][0],c[_][1]),t.stroke()};r(A.annotations.indexFinger),r(A.annotations.middleFinger),r(A.annotations.ringFinger),r(A.annotations.pinky),r(A.annotations.thumb)}}}}async function Ct(n,e){if(!e||!n||!(n instanceof HTMLCanvasElement))return;let t=n.getContext("2d");if(!!t){t.lineJoin="round",t.font=w.font;for(let A of e)if(w.drawBoxes){if(t.strokeStyle=w.color,t.fillStyle=w.color,d0(t,A.box[0],A.box[1],A.box[2]-A.box[0],A.box[3]-A.box[1]),w.drawLabels){let r=`${Math.round(100*A.score)}% ${A.label}`;w.shadowColor&&w.shadowColor!==""&&(t.fillStyle=w.shadowColor,t.fillText(r,A.box[0]+3,1+A.box[1]+w.lineHeight,A.box[2])),t.fillStyle=w.labelColor,t.fillText(r,A.box[0]+2,0+A.box[1]+w.lineHeight,A.box[2])}t.stroke()}}}async function Jn(n,e){if(!n||!e||!(n instanceof HTMLCanvasElement)||!(e instanceof HTMLCanvasElement))return;let t=n.getContext("2d");t==null||t.drawImage(n,0,0)}async function Kn(n,e){!e||!n||n instanceof HTMLCanvasElement&&(Xt(n,e.face),Ft(n,e.body),qt(n,e.hand),Ht(n,e.gesture),Ct(n,e.object))}var R=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Te(...n){let e=t=>t&&typeof t=="object";return n.reduce((t,A)=>(Object.keys(A||{}).forEach(r=>{let c=t[r],_=A[r];Array.isArray(c)&&Array.isArray(_)?t[r]=c.concat(..._):e(c)&&e(_)?t[r]=Te(c,_):t[r]=_}),t),{})}var e1,P,pe,Pe,ve,le,O,t1,ze,n1,Me,r1,A1,c1,p0=class{constructor(e={}){e1.set(this,void 0);P.set(this,void 0);pe.set(this,void 0);Pe.set(this,void 0);ve.set(this,void 0);le.set(this,void 0);O.set(this,(...e)=>{if(!u(this,Pe))return;let t=this.tf.engine().state.numTensors,A=u(this,pe);Ae(this,pe,t);let r=t-A;r!==0&&g(...e,r)});t1.set(this,e=>{if(!u(this,ve))return null;if(!e)return"input is not defined";if(this.tf.ENV.flags.IS_NODE&&!(e instanceof m0.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(t){return"backend not loaded"}return 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k=u(this,n1).call(this,b.mesh);u(this,O).call(this,"Start Age:"),this.config.async?A=this.config.face.age.enabled?p1(b.image,this.config):{}:(this.state="run:age",t=R(),A=this.config.face.age.enabled?await p1(b.image,this.config):{},u(this,P).age=Math.trunc(R()-t)),u(this,O).call(this,"Start Gender:"),this.config.async?r=this.config.face.gender.enabled?z1(b.image,this.config):{}:(this.state="run:gender",t=R(),r=this.config.face.gender.enabled?await z1(b.image,this.config):{},u(this,P).gender=Math.trunc(R()-t)),u(this,O).call(this,"Start Emotion:"),this.config.async?c=this.config.face.emotion.enabled?S1(b.image,this.config):{}:(this.state="run:emotion",t=R(),c=this.config.face.emotion.enabled?await S1(b.image,this.config):{},u(this,P).emotion=Math.trunc(R()-t)),u(this,O).call(this,"End Emotion:"),u(this,O).call(this,"Start Embedding:"),this.config.async?_=this.config.face.embedding.enabled?k1(b,this.config):[]:(this.state="run:embedding",t=R(),_=this.config.face.embedding.enabled?await k1(b,this.config):[],u(this,P).embedding=Math.trunc(R()-t)),u(this,O).call(this,"End Emotion:"),this.config.async&&([A,r,c,_]=await Promise.all([A,r,c,_])),u(this,O).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((a=b==null?void 0:b.annotations)==null?void 0:a.leftEyeIris)&&((i=b==null?void 0:b.annotations)==null?void 0:i.rightEyeIris)&&(delete b.annotations.leftEyeIris,delete b.annotations.rightEyeIris);let I=((l=b.annotations)==null?void 0:l.leftEyeIris)&&((d=b.annotations)==null?void 0:d.rightEyeIris)?11.7*Math.max(Math.abs(b.annotations.leftEyeIris[3][0]-b.annotations.leftEyeIris[1][0]),Math.abs(b.annotations.rightEyeIris[4][1]-b.annotations.rightEyeIris[2][1])):0;h.push({...b,age:A.age,gender:r.gender,genderConfidence:r.confidence,emotion:c,embedding:_,iris:I!==0?Math.trunc(I)/100:0,angle:k,tensor:this.config.face.detector.return?(f=b.image)==null?void 0:f.squeeze():null}),(x=b.image)==null||x.dispose(),u(this,O).call(this,"End Face")}return u(this,O).call(this,"End 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this.detect(c,this.config);e(h)},t?r.src=t:e(null)}));c1.set(this,async()=>{let e=_=>Buffer.from(_,"base64"),t=this.config.warmup==="face"?e(De):e(Ge),A=m0.node.decodeJpeg(t),r=A.expandDims(0);this.tf.dispose(A);let c=await this.detect(r,this.config);return this.tf.dispose(r),c});this.tf=m0,this.draw=l0,Ae(this,e1,y0),this.version=w0,this.config=Te(S,e),this.state="idle",Ae(this,pe,0),Ae(this,Pe,!1),Ae(this,ve,!1),Ae(this,le,!0),Ae(this,P,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=t=>a0(t,this.config),this.classes={facemesh:u0,age:m1,gender:b1,emotion:M1,body:this.config.body.modelPath.includes("posenet")?J1:c0,hand:e0,nanodet:o0},this.sysinfo=z0()}profileData(){return this.config.profile?f1:{}}simmilarity(e,t){return this.config.face.embedding.enabled?W1(e,t):0}enhance(e){return O1(e)}match(e,t,A=0){return F0(e,t,A)}async load(e={}){this.state="load";let t=R();e&&(this.config=Te(this.config,e)),u(this,le)&&(this.config.debug&&g(`version: ${this.version}`),this.config.debug&&g(`tfjs version: ${this.tf.version_core}`),this.config.debug&&g("platform:",this.sysinfo.platform),this.config.debug&&g("agent:",this.sysinfo.agent),await u(this,ze).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&g("configuration:",this.config),this.config.debug&&g("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?u0.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?u1(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?v1(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?N1(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?j1(this.config):null),this.models.handpose||(this.config.hand.enabled?A0(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?U1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?_0(this.config):null),this.models.nanodet||(this.config.object.enabled?i0(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await u0.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await u1(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await v1(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await N1(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await j1(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await A0(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await U1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await _0(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await i0(this.config))),u(this,le)&&(this.config.debug&&g("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),Ae(this,le,!1));let A=Math.trunc(R()-t);A>(u(this,P).load||0)&&(u(this,P).load=A)}async detect(e,t={}){return new Promise(async A=>{var d,f,x,b;this.state="config";let r;this.config=Te(this.config,t),this.state="check";let c=u(this,t1).call(this,e);c&&(g(c,e),A({error:c}));let _=R();await u(this,ze).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),u(this,O).call(this,"Start Scope:"),r=R();let h=a0(e,this.config);if(!h||!h.tensor){g("could not convert input to tensor"),A({error:"could not convert input to tensor"});return}u(this,P).image=Math.trunc(R()-r),u(this,O).call(this,"Get Image:");let o,s,a,i;this.config.async?(a=this.config.face.enabled?u(this,Me).call(this,h.tensor):[],u(this,P).face&&delete u(this,P).face):(this.state="run:face",r=R(),a=this.config.face.enabled?await u(this,Me).call(this,h.tensor):[],u(this,P).face=Math.trunc(R()-r)),u(this,O).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?(d=this.models.posenet)==null?void 0:d.estimatePoses(h.tensor,this.config):[]:o=this.config.body.enabled?h0(h.tensor,this.config):[],u(this,P).body&&delete u(this,P).body):(this.state="run:body",r=R(),this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?await((f=this.models.posenet)==null?void 0:f.estimatePoses(h.tensor,this.config)):[]:o=this.config.body.enabled?await h0(h.tensor,this.config):[],u(this,P).body=Math.trunc(R()-r)),u(this,O).call(this,"End Body:"),u(this,O).call(this,"Start Hand:"),this.config.async?(s=this.config.hand.enabled?(x=this.models.handpose)==null?void 0:x.estimateHands(h.tensor,this.config):[],u(this,P).hand&&delete u(this,P).hand):(this.state="run:hand",r=R(),s=this.config.hand.enabled?await((b=this.models.handpose)==null?void 0:b.estimateHands(h.tensor,this.config)):[],u(this,P).hand=Math.trunc(R()-r)),u(this,O).call(this,"End Hand:"),u(this,O).call(this,"Start Object:"),this.config.async?(i=this.config.object.enabled?x0(h.tensor,this.config):[],u(this,P).object&&delete u(this,P).object):(this.state="run:object",r=R(),i=this.config.object.enabled?await x0(h.tensor,this.config):[],u(this,P).object=Math.trunc(R()-r)),u(this,O).call(this,"End Object:"),this.config.async&&([a,o,s,i]=await Promise.all([a,o,s,i])),h.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),u(this,O).call(this,"End Scope:");let l=[];this.config.gesture.enabled&&(r=R(),l=[...pt(a),...ut(o),...gt(s),...bt(a)],this.config.async?u(this,P).gesture&&delete u(this,P).gesture:u(this,P).gesture=Math.trunc(R()-r)),u(this,P).total=Math.trunc(R()-_),this.state="idle",A({face:a,body:o,hand:s,gesture:l,object:i,performance:u(this,P),canvas:h.canvas})})}async warmup(e={}){let t=R();e&&(this.config=Te(this.config,e));let A=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await u(this,r1).call(this):typeof Image!="undefined"?r=await u(this,A1).call(this):r=await u(this,c1).call(this),this.config.videoOptimized=A;let c=R();return this.config.debug&&g("Warmup",this.config.warmup,Math.round(c-t),"ms",r),r}};e1=new WeakMap,P=new WeakMap,pe=new WeakMap,Pe=new WeakMap,ve=new WeakMap,le=new WeakMap,O=new WeakMap,t1=new WeakMap,ze=new WeakMap,n1=new WeakMap,Me=new WeakMap,r1=new WeakMap,A1=new WeakMap,c1=new WeakMap;0&&(module.exports={Human});
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dt={};U(dt,{all:()=>Kn,body:()=>F0,canvas:()=>Cn,drawOptions:()=>y,face:()=>X0,gesture:()=>H0,hand:()=>q0,object:()=>B0});var y={color:"rgba(173, 216, 230, 0.3)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",font:'small-caps 16px "Segoe UI"',lineHeight:20,lineWidth:6,pointSize:2,roundRect:28,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawPolygons:!0,fillPolygons:!1,useDepth:!0,useCurves:!1,bufferedOutput:!1,useRawBoxes:!1};function $e(n,e,t,A=null){n.fillStyle=y.useDepth&&A?`rgba(${127.5+2*(A||0)}, ${127.5-2*(A||0)}, 255, 0.3)`:y.color,n.beginPath(),n.arc(e,t,y.pointSize,0,2*Math.PI),n.fill()}function pe(n,e,t,A,r){if(n.beginPath(),y.useCurves){let c=(e+e+A)/2,_=(t+t+r)/2;n.ellipse(c,_,A/2,r/2,0,0,2*Math.PI)}else 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0:s.estimateFaces(e,this.config));if(u(this,P).face=Math.trunc(M()-t),!o)return[];for(let b of o){if(u(this,k).call(this,"Get Face"),!b.image||b.image.isDisposedInternal){g("Face object is disposed:",b.image);continue}let j=u(this,r1).call(this,b.mesh);u(this,k).call(this,"Start Age:"),this.config.async?A=this.config.face.age.enabled?b1(b.image,this.config):{}:(this.state="run:age",t=M(),A=this.config.face.age.enabled?await b1(b.image,this.config):{},u(this,P).age=Math.trunc(M()-t)),u(this,k).call(this,"Start Gender:"),this.config.async?r=this.config.face.gender.enabled?R1(b.image,this.config):{}:(this.state="run:gender",t=M(),r=this.config.face.gender.enabled?await R1(b.image,this.config):{},u(this,P).gender=Math.trunc(M()-t)),u(this,k).call(this,"Start Emotion:"),this.config.async?c=this.config.face.emotion.enabled?j1(b.image,this.config):{}:(this.state="run:emotion",t=M(),c=this.config.face.emotion.enabled?await j1(b.image,this.config):{},u(this,P).emotion=Math.trunc(M()-t)),u(this,k).call(this,"End Emotion:"),u(this,k).call(this,"Start Embedding:"),this.config.async?_=this.config.face.embedding.enabled?I1(b,this.config):[]:(this.state="run:embedding",t=M(),_=this.config.face.embedding.enabled?await I1(b,this.config):[],u(this,P).embedding=Math.trunc(M()-t)),u(this,k).call(this,"End Emotion:"),this.config.async&&([A,r,c,_]=await Promise.all([A,r,c,_])),u(this,k).call(this,"Finish Face:"),!this.config.face.iris.enabled&&((a=b==null?void 0:b.annotations)==null?void 0:a.leftEyeIris)&&((i=b==null?void 0:b.annotations)==null?void 0:i.rightEyeIris)&&(delete b.annotations.leftEyeIris,delete b.annotations.rightEyeIris);let I=((l=b.annotations)==null?void 0:l.leftEyeIris)&&((m=b.annotations)==null?void 0:m.rightEyeIris)?11.7*Math.max(Math.abs(b.annotations.leftEyeIris[3][0]-b.annotations.leftEyeIris[1][0]),Math.abs(b.annotations.rightEyeIris[4][1]-b.annotations.rightEyeIris[2][1])):0;h.push({...b,age:A.age,gender:r.gender,genderConfidence:r.confidence,emotion:c,embedding:_,iris:I!==0?Math.trunc(I)/100:0,angle:j,tensor:this.config.face.detector.return?(f=b.image)==null?void 0:f.squeeze():null}),(x=b.image)==null||x.dispose(),u(this,k).call(this,"End Face")}return u(this,k).call(this,"End FaceMesh:"),this.config.async&&(u(this,P).face&&delete u(this,P).face,u(this,P).age&&delete u(this,P).age,u(this,P).gender&&delete u(this,P).gender,u(this,P).emotion&&delete u(this,P).emotion),h});A1.set(this,async()=>{let e=(r,c="application/octet-stream")=>fetch(`data:${c};base64,${r}`).then(_=>_.blob()),t,A;switch(this.config.warmup){case"face":t=await e(Ge);break;case"full":t=await e(Qe);break;default:t=null}if(t){let r=await createImageBitmap(t);A=await this.detect(r,this.config),r.close()}return A});c1.set(this,async()=>new Promise(e=>{let t,A=0;switch(this.config.warmup){case"face":A=256,t="data:image/jpeg;base64,"+Ge;break;case"full":case"body":A=1200,t="data:image/jpeg;base64,"+Qe;break;default:t=null}let r=new Image;r.onload=async()=>{let c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(A,A):document.createElement("canvas");c.width=r.naturalWidth,c.height=r.naturalHeight;let _=c.getContext("2d");_==null||_.drawImage(r,0,0);let h=await this.detect(c,this.config);e(h)},t?r.src=t:e(null)}));_1.set(this,async()=>{let e=_=>Buffer.from(_,"base64"),t=this.config.warmup==="face"?e(Ge):e(Qe),A=mt.node.decodeJpeg(t),r=A.expandDims(0);this.tf.dispose(A);let c=await this.detect(r,this.config);return this.tf.dispose(r),c});this.tf=mt,this.draw=dt,Ae(this,t1,wt),this.version=lt,this.config=Pe(S,e),this.state="idle",Ae(this,be,0),Ae(this,ve,!1),Ae(this,ze,!1),Ae(this,le,!0),Ae(this,P,{}),this.models={face:null,posenet:null,blazepose:null,handpose:null,iris:null,age:null,gender:null,emotion:null,embedding:null,nanodet:null},this.image=t=>yt(t,this.config),this.classes={facemesh:ut,age:u1,gender:g1,emotion:M1,body:this.config.body.modelPath.includes("posenet")?K1:_t,hand:tt,nanodet:st},this.sysinfo=zt()}profileData(){return this.config.profile?m1:{}}simmilarity(e,t){return this.config.face.embedding.enabled?O1(e,t):0}enhance(e){return k1(e)}match(e,t,A=0){return Ft(e,t,A)}async load(e={}){this.state="load";let t=M();e&&(this.config=Pe(this.config,e)),u(this,le)&&(this.config.debug&&g(`version: ${this.version}`),this.config.debug&&g(`tfjs version: ${this.tf.version_core}`),this.config.debug&&g("platform:",this.sysinfo.platform),this.config.debug&&g("agent:",this.sysinfo.agent),await u(this,Re).call(this,!0),this.tf.ENV.flags.IS_BROWSER&&(this.config.debug&&g("configuration:",this.config),this.config.debug&&g("tf flags:",this.tf.ENV.flags))),this.config.async?[this.models.face,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.handpose,this.models.posenet,this.models.blazepose,this.models.nanodet]=await Promise.all([this.models.face||(this.config.face.enabled?ut.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?p1(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?z1(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?S1(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?W1(this.config):null),this.models.handpose||(this.config.hand.enabled?ct(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("posenet")?D1(this.config):null),this.models.posenet||(this.config.body.enabled&&this.config.body.modelPath.includes("blazepose")?ht(this.config):null),this.models.nanodet||(this.config.object.enabled?xt(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await ut.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await p1(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await z1(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await S1(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await W1(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await ct(this.config)),this.config.body.enabled&&!this.models.posenet&&this.config.body.modelPath.includes("posenet")&&(this.models.posenet=await D1(this.config)),this.config.body.enabled&&!this.models.blazepose&&this.config.body.modelPath.includes("blazepose")&&(this.models.blazepose=await ht(this.config)),this.config.object.enabled&&!this.models.nanodet&&(this.models.nanodet=await xt(this.config))),u(this,le)&&(this.config.debug&&g("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),Ae(this,le,!1));let A=Math.trunc(M()-t);A>(u(this,P).load||0)&&(u(this,P).load=A)}async detect(e,t={}){return new Promise(async A=>{var f,x,b,j;this.state="config";let r;this.config=Pe(this.config,t),this.state="check";let c=u(this,n1).call(this,e);c&&(g(c,e),A({error:c}));let _=M();await u(this,Re).call(this),await this.load(),this.config.scoped&&this.tf.engine().startScope(),u(this,k).call(this,"Start Scope:"),r=M();let h=yt(e,this.config);if(!h||!h.tensor){g("could not convert input to tensor"),A({error:"could not convert input to tensor"});return}u(this,P).image=Math.trunc(M()-r),u(this,k).call(this,"Get Image:");let o,s,a,i;this.config.async?(a=this.config.face.enabled?u(this,Me).call(this,h.tensor):[],u(this,P).face&&delete u(this,P).face):(this.state="run:face",r=M(),a=this.config.face.enabled?await u(this,Me).call(this,h.tensor):[],u(this,P).face=Math.trunc(M()-r)),u(this,k).call(this,"Start Body:"),this.config.async?(this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?(f=this.models.posenet)==null?void 0:f.estimatePoses(h.tensor,this.config):[]:o=this.config.body.enabled?ot(h.tensor,this.config):[],u(this,P).body&&delete u(this,P).body):(this.state="run:body",r=M(),this.config.body.modelPath.includes("posenet")?o=this.config.body.enabled?await((x=this.models.posenet)==null?void 0:x.estimatePoses(h.tensor,this.config)):[]:o=this.config.body.enabled?await ot(h.tensor,this.config):[],u(this,P).body=Math.trunc(M()-r)),u(this,k).call(this,"End Body:"),u(this,k).call(this,"Start Hand:"),this.config.async?(s=this.config.hand.enabled?(b=this.models.handpose)==null?void 0:b.estimateHands(h.tensor,this.config):[],u(this,P).hand&&delete u(this,P).hand):(this.state="run:hand",r=M(),s=this.config.hand.enabled?await((j=this.models.handpose)==null?void 0:j.estimateHands(h.tensor,this.config)):[],u(this,P).hand=Math.trunc(M()-r)),u(this,k).call(this,"End Hand:"),u(this,k).call(this,"Start Object:"),this.config.async?(i=this.config.object.enabled?at(h.tensor,this.config):[],u(this,P).object&&delete u(this,P).object):(this.state="run:object",r=M(),i=this.config.object.enabled?await at(h.tensor,this.config):[],u(this,P).object=Math.trunc(M()-r)),u(this,k).call(this,"End Object:"),this.config.async&&([a,o,s,i]=await Promise.all([a,o,s,i])),h.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),u(this,k).call(this,"End Scope:");let l=[];this.config.gesture.enabled&&(r=M(),l=[...p0(a),...u0(o),...g0(s),...b0(a)],this.config.async?u(this,P).gesture&&delete u(this,P).gesture:u(this,P).gesture=Math.trunc(M()-r)),u(this,P).total=Math.trunc(M()-_),this.state="idle";let m={face:a,body:o,hand:s,gesture:l,object:i,performance:u(this,P),canvas:h.canvas};A(m)})}async warmup(e={}){let t=M();e&&(this.config=Pe(this.config,e));let A=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await u(this,A1).call(this):typeof Image!="undefined"?r=await u(this,c1).call(this):r=await u(this,_1).call(this),this.config.videoOptimized=A;let c=M();return this.config.debug&&g("Warmup",this.config.warmup,Math.round(c-t),"ms",r),r}};t1=new WeakMap,P=new WeakMap,be=new WeakMap,ve=new WeakMap,ze=new WeakMap,le=new WeakMap,k=new WeakMap,n1=new WeakMap,Re=new WeakMap,r1=new WeakMap,Me=new WeakMap,A1=new WeakMap,c1=new WeakMap,_1=new WeakMap;0&&(module.exports={Human});
 //# sourceMappingURL=human.node.js.map
diff --git a/dist/human.node.js.map b/dist/human.node.js.map
index 4f1c0e9c..3712e434 100644
--- a/dist/human.node.js.map
+++ b/dist/human.node.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["../src/tfjs/tf-node.ts", "../src/blazeface/facemesh.ts", "../src/posenet/keypoints.ts", "../src/human.ts", "../src/log.ts", "../src/sysinfo.ts", "../src/tfjs/backend.ts", "../src/blazeface/blazeface.ts", "../src/blazeface/facepipeline.ts", "../src/blazeface/box.ts", "../src/blazeface/util.ts", "../src/blazeface/coords.ts", "../src/age/age.ts", "../src/profile.ts", "../src/gender/gender.ts", "../src/emotion/emotion.ts", "../src/embedding/embedding.ts", "../src/posenet/posenet.ts", "../src/posenet/modelBase.ts", "../src/posenet/heapSort.ts", "../src/posenet/buildParts.ts", "../src/posenet/decodePose.ts", "../src/posenet/vectors.ts", "../src/posenet/decoders.ts", "../src/posenet/decodeMultiple.ts", "../src/posenet/util.ts", "../src/handpose/handpose.ts", "../src/handpose/handdetector.ts", "../src/handpose/box.ts", "../src/handpose/handpipeline.ts", "../src/handpose/util.ts", "../src/handpose/anchors.ts", "../src/blazepose/blazepose.ts", "../src/blazepose/annotations.ts", "../src/nanodet/nanodet.ts", "../src/gesture/gesture.ts", "../src/image.ts", "../src/imagefx.js", "../config.ts", "../src/sample.ts", "../src/draw.ts"],
-  "sourcesContent": ["export * from '@tensorflow/tfjs-node';\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - prediction.box.startPoint[0],\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - prediction.box.startPoint[1],\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0] / input.shape[2]),\n        Math.max(0, prediction.box.startPoint[1] / input.shape[1]),\n        Math.min(input.shape[1], (prediction.box.endPoint[0]) - prediction.box.startPoint[0]) / input.shape[2],\n        Math.min(input.shape[2], (prediction.box.endPoint[1]) - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        mesh,\n        boxRaw,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      resolve({ face: faceRes, body: bodyRes, hand: handRes, gesture: gestureRes, object: objectRes, performance: this.#perf, canvas: process.canvas });\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 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0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - prediction.box.topLeft[0],\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - prediction.box.topLeft[1],\n      ] : 0;\n      hands.push({ confidence: prediction.confidence, box, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            boxRaw[0] * outputShape[0],\n            boxRaw[1] * outputShape[1],\n            boxRaw[2] * outputShape[0],\n            boxRaw[3] * outputShape[1],\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n      // rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2] - h.box[0], h.box[3] - h.box[1]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
-  "mappings": 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+  "sourcesContent": ["export * from '@tensorflow/tfjs-node';\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as facepipeline from './facepipeline';\nimport * as coords from './coords';\n\nexport class MediaPipeFaceMesh {\n  facePipeline: any;\n  config: any;\n\n  constructor(blazeFace, blazeMeshModel, irisModel, config) {\n    this.facePipeline = new facepipeline.Pipeline(blazeFace, blazeMeshModel, irisModel);\n    this.config = config;\n  }\n\n  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {\n    const predictions = await this.facePipeline.predict(input, config);\n    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];\n    for (const prediction of (predictions || [])) {\n      if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing\n      const mesh = prediction.coords ? prediction.coords.arraySync() : [];\n      const meshRaw = mesh.map((pt) => [\n        pt[0] / input.shape[2],\n        pt[1] / input.shape[1],\n        pt[2] / this.facePipeline.meshSize,\n      ]);\n      const annotations = {};\n      if (mesh && mesh.length > 0) {\n        for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.startPoint[0]),\n        Math.max(0, prediction.box.startPoint[1]),\n        Math.min(input.shape[1], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),\n        Math.min(input.shape[2], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),\n      ] : 0;\n      const boxRaw = prediction.box ? [\n        prediction.box.startPoint[0] / input.shape[2],\n        prediction.box.startPoint[1] / input.shape[1],\n        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],\n        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],\n      ] : [];\n      results.push({\n        confidence: prediction.faceConfidence || prediction.boxConfidence || 0,\n        boxConfidence: prediction.boxConfidence,\n        faceConfidence: prediction.faceConfidence,\n        box,\n        boxRaw,\n        mesh,\n        meshRaw,\n        annotations,\n        image: prediction.image ? prediction.image.clone() : null,\n      });\n      if (prediction.coords) prediction.coords.dispose();\n      if (prediction.image) prediction.image.dispose();\n    }\n    return results;\n  }\n}\n\nlet faceModels = [null, null, null];\nexport async function load(config) {\n  // @ts-ignore\n  faceModels = await Promise.all([\n    (!faceModels[0] && config.face.enabled) ? blazeface.load(config) : null,\n    (!faceModels[1] && config.face.mesh.enabled) ? tf.loadGraphModel(config.face.mesh.modelPath, { fromTFHub: config.face.mesh.modelPath.includes('tfhub.dev') }) : null,\n    (!faceModels[2] && config.face.iris.enabled) ? tf.loadGraphModel(config.face.iris.modelPath, { fromTFHub: config.face.iris.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const faceMesh = new MediaPipeFaceMesh(faceModels[0], faceModels[1], faceModels[2], config);\n  if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return faceMesh;\n}\n\nexports.triangulation = coords.TRI468;\n", "export const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const NUM_KEYPOINTS = exports.partNames.length; // 17 keypoints\n\nexport const partIds = exports.partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport const partChannels = [\n  'left_face',\n  'right_face',\n  'right_upper_leg_front',\n  'right_lower_leg_back',\n  'right_upper_leg_back',\n  'left_lower_leg_front',\n  'left_upper_leg_front',\n  'left_upper_leg_back',\n  'left_lower_leg_back',\n  'right_feet',\n  'right_lower_leg_front',\n  'left_feet',\n  'torso_front',\n  'torso_back',\n  'right_upper_arm_front',\n  'right_upper_arm_back',\n  'right_lower_arm_back',\n  'left_lower_arm_front',\n  'left_upper_arm_front',\n  'left_upper_arm_back',\n  'left_lower_arm_back',\n  'right_hand',\n  'right_lower_arm_front',\n  'left_hand',\n];\n", "import { log } from './log';\nimport * as sysinfo from './sysinfo';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as backend from './tfjs/backend';\nimport * as facemesh from './blazeface/facemesh';\nimport * as age from './age/age';\nimport * as gender from './gender/gender';\nimport * as emotion from './emotion/emotion';\nimport * as embedding from './embedding/embedding';\nimport * as posenet from './posenet/posenet';\nimport * as handpose from './handpose/handpose';\nimport * as blazepose from './blazepose/blazepose';\nimport * as nanodet from './nanodet/nanodet';\nimport * as gesture from './gesture/gesture';\nimport * as image from './image';\nimport * as profile from './profile';\nimport * as config from '../config';\nimport * as sample from './sample';\nimport * as app from '../package.json';\nimport * as draw from './draw';\n\n// helper function: gets elapsed time on both browser and nodejs\nconst now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\ntype Tensor = {};\ntype Model = {};\nexport type Result = {\n  face: Array<{\n    confidence: Number,\n    boxConfidence: Number,\n    faceConfidence: Number,\n    box: [Number, Number, Number, Number],\n    mesh: Array<[Number, Number, Number]>\n    meshRaw: Array<[Number, Number, Number]>\n    boxRaw: [Number, Number, Number, Number],\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n    age: Number,\n    gender: String,\n    genderConfidence: Number,\n    emotion: Array<{ score: Number, emotion: String }>,\n    embedding: Array<Number>,\n    iris: Number,\n    angle: { roll: Number, yaw: Number, pitch: Number },\n  }>,\n  body: Array<{\n    id: Number,\n    part: String,\n    position: { x: Number, y: Number, z: Number },\n    score: Number,\n    presence: Number }>,\n  hand: Array<{\n    confidence: Number,\n    box: [Number, Number, Number, Number],\n    boxRaw: [Number, Number, Number, Number],\n    landmarks: Array<[Number, Number, Number]>,\n    annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,\n  }>,\n  gesture: Array<{\n    part: String,\n    gesture: String,\n  }>,\n  object: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }>,\n  performance: { any },\n  canvas: OffscreenCanvas | HTMLCanvasElement,\n}\n\nexport type { default as Config } from '../config';\n\n// helper function: perform deep merge of multiple objects so it allows full inheriance with overrides\nfunction mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\nexport class Human {\n  version: String;\n  config: typeof config.default;\n  state: String;\n  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };\n  // classes\n  tf: typeof tf;\n  draw: { drawOptions?: typeof draw.drawOptions, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };\n  // models\n  models: {\n    face: facemesh.MediaPipeFaceMesh | null,\n    posenet: posenet.PoseNet | null,\n    blazepose: Model | null,\n    handpose: handpose.HandPose | null,\n    iris: Model | null,\n    age: Model | null,\n    gender: Model | null,\n    emotion: Model | null,\n    embedding: Model | null,\n    nanodet: Model | null,\n  };\n  classes: {\n    facemesh: typeof facemesh;\n    age: typeof age;\n    gender: typeof gender;\n    emotion: typeof emotion;\n    body: typeof posenet | typeof blazepose;\n    hand: typeof handpose;\n    nanodet: typeof nanodet;\n  };\n  sysinfo: { platform: String, agent: String };\n  #package: any;\n  #perf: any;\n  #numTensors: number;\n  #analyzeMemoryLeaks: Boolean;\n  #checkSanity: Boolean;\n  #firstRun: Boolean;\n  // definition end\n\n  constructor(userConfig = {}) {\n    this.tf = tf;\n    this.draw = draw;\n    this.#package = app;\n    this.version = app.version;\n    this.config = mergeDeep(config.default, userConfig);\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.#firstRun = true;\n    this.#perf = {};\n    // object that contains all initialized models\n    this.models = {\n      face: null,\n      posenet: null,\n      blazepose: null,\n      handpose: null,\n      iris: null,\n      age: null,\n      gender: null,\n      emotion: null,\n      embedding: null,\n      nanodet: null,\n    };\n    // export access to image processing\n    // @ts-ignore\n    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);\n    // export raw access to underlying models\n    this.classes = {\n      facemesh,\n      age,\n      gender,\n      emotion,\n      body: this.config.body.modelPath.includes('posenet') ? posenet : blazepose,\n      hand: handpose,\n      nanodet,\n    };\n    // include platform info\n    this.sysinfo = sysinfo.info();\n  }\n\n  profileData(): { newBytes, newTensors, peakBytes, numKernelOps, timeKernelOps, slowestKernelOps, largestKernelOps } | {} {\n    if (this.config.profile) return profile.data;\n    return {};\n  }\n\n  // helper function: measure tensor leak\n  /** @hidden */\n  #analyze = (...msg) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const current = this.tf.engine().state.numTensors;\n    const previous = this.#numTensors;\n    this.#numTensors = current;\n    const leaked = current - previous;\n    if (leaked !== 0) log(...msg, leaked);\n  }\n\n  // quick sanity check on inputs\n  /** @hidden */\n  #sanity = (input): null | String => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  }\n\n  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {\n    if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);\n    return 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return embedding.enhance(input);\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  match(faceEmbedding: Array<Number>, db: Array<{ name: String, source: String | undefined, embedding: Array<Number> }>, threshold = 0): { name: String, source: String | undefined, simmilarity: Number, embedding: Array<Number> } {\n    return embedding.match(faceEmbedding, db, threshold);\n  }\n\n  // preload models, not explicitly required as it's done automatically on first use\n  async load(userConfig: Object = {}) {\n    this.state = 'load';\n    const timeStamp = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n\n    if (this.#firstRun) {\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version_core}`);\n      if (this.config.debug) log('platform:', this.sysinfo.platform);\n      if (this.config.debug) log('agent:', this.sysinfo.agent);\n\n      await this.#checkBackend(true);\n      if (this.tf.ENV.flags.IS_BROWSER) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('tf flags:', this.tf.ENV.flags);\n      }\n    }\n    if (this.config.async) {\n      [\n        this.models.face,\n        this.models.age,\n        this.models.gender,\n        this.models.emotion,\n        this.models.embedding,\n        this.models.handpose,\n        this.models.posenet,\n        this.models.blazepose,\n        this.models.nanodet,\n      ] = await Promise.all([\n        this.models.face || (this.config.face.enabled ? facemesh.load(this.config) : null),\n        this.models.age || ((this.config.face.enabled && this.config.face.age.enabled) ? age.load(this.config) : null),\n        this.models.gender || ((this.config.face.enabled && this.config.face.gender.enabled) ? gender.load(this.config) : null),\n        this.models.emotion || ((this.config.face.enabled && this.config.face.emotion.enabled) ? emotion.load(this.config) : null),\n        this.models.embedding || ((this.config.face.enabled && this.config.face.embedding.enabled) ? embedding.load(this.config) : null),\n        this.models.handpose || (this.config.hand.enabled ? handpose.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('posenet') ? posenet.load(this.config) : null),\n        this.models.posenet || (this.config.body.enabled && this.config.body.modelPath.includes('blazepose') ? blazepose.load(this.config) : null),\n        this.models.nanodet || (this.config.object.enabled ? nanodet.load(this.config) : null),\n      ]);\n    } else {\n      if (this.config.face.enabled && !this.models.face) this.models.face = await facemesh.load(this.config);\n      if (this.config.face.enabled && this.config.face.age.enabled && !this.models.age) this.models.age = await age.load(this.config);\n      if (this.config.face.enabled && this.config.face.gender.enabled && !this.models.gender) this.models.gender = await gender.load(this.config);\n      if (this.config.face.enabled && this.config.face.emotion.enabled && !this.models.emotion) this.models.emotion = await emotion.load(this.config);\n      if (this.config.face.enabled && this.config.face.embedding.enabled && !this.models.embedding) this.models.embedding = await embedding.load(this.config);\n      if (this.config.hand.enabled && !this.models.handpose) this.models.handpose = await handpose.load(this.config);\n      if (this.config.body.enabled && !this.models.posenet && this.config.body.modelPath.includes('posenet')) this.models.posenet = await posenet.load(this.config);\n      if (this.config.body.enabled && !this.models.blazepose && this.config.body.modelPath.includes('blazepose')) this.models.blazepose = await blazepose.load(this.config);\n      if (this.config.object.enabled && !this.models.nanodet) this.models.nanodet = await nanodet.load(this.config);\n    }\n\n    if (this.#firstRun) {\n      if (this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors');\n      this.#firstRun = false;\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.#perf.load || 0)) this.#perf.load = current;\n  }\n\n  // check if backend needs initialization if it changed\n  /** @hidden */\n  #checkBackend = async (force = false) => {\n    if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {\n      const timeStamp = now();\n      this.state = 'backend';\n      /* force backend reload\n      if (this.config.backend in tf.engine().registry) {\n        const backendFactory = tf.findBackendFactory(this.config.backend);\n        tf.removeBackend(this.config.backend);\n        tf.registerBackend(this.config.backend, backendFactory);\n      } else {\n        log('Backend not registred:', this.config.backend);\n      }\n      */\n\n      if (this.config.backend && this.config.backend !== '') {\n        if (this.config.debug) log('setting backend:', this.config.backend);\n\n        if (this.config.backend === 'wasm') {\n          if (this.config.debug) log('wasm path:', this.config.wasmPath);\n          this.tf.setWasmPaths(this.config.wasmPath);\n          const simd = await this.tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n          const mt = await this.tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n          if (this.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n          if (!simd) log('warning: wasm simd support is not enabled');\n        }\n\n        if (this.config.backend === 'humangl') backend.register();\n        try {\n          await this.tf.setBackend(this.config.backend);\n        } catch (err) {\n          log('error: cannot set backend:', this.config.backend, err);\n        }\n      }\n      this.tf.enableProdMode();\n      /* debug mode is really too mcuh\n      tf.enableDebugMode();\n      */\n      if (this.tf.getBackend() === 'webgl') {\n        if (this.config.deallocate) {\n          log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', this.config.deallocate);\n          this.tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', this.config.deallocate ? 0 : -1);\n        }\n        // this.tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n        // this.tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n        const gl = await this.tf.backend().getGPGPUContext().gl;\n        if (this.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n      await this.tf.ready();\n      this.#perf.backend = Math.trunc(now() - timeStamp);\n    }\n  }\n\n  /** @hidden */\n  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {\n    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n    const angle = {\n      // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees\n      // value of 0 means center\n      // roll is face lean left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye\n      // yaw is face turn left/right\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye\n      // pitch is face move up/down\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face\n    };\n    return angle;\n  }\n\n  /** @hidden */\n  #detectFace = async (input): Promise<any> => {\n    // run facemesh, includes blazeface and iris\n    // eslint-disable-next-line no-async-promise-executor\n    let timeStamp;\n    let ageRes;\n    let genderRes;\n    let emotionRes;\n    let embeddingRes;\n    const faceRes: Array<{\n      confidence: Number,\n      boxConfidence: Number,\n      faceConfidence: Number,\n      box: [Number, Number, Number, Number],\n      mesh: Array<[Number, Number, Number]>\n      meshRaw: Array<[Number, Number, Number]>\n      boxRaw: [Number, Number, Number, Number],\n      annotations: any,\n      age: Number,\n      gender: String,\n      genderConfidence: Number,\n      emotion: String,\n      embedding: any,\n      iris: Number,\n      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },\n      tensor: Tensor,\n    }> = [];\n\n    this.state = 'run:face';\n    timeStamp = now();\n    const faces = await this.models.face?.estimateFaces(input, this.config);\n    this.#perf.face = Math.trunc(now() - timeStamp);\n    if (!faces) return [];\n    for (const face of faces) {\n      this.#analyze('Get Face');\n\n      // is something went wrong, skip the face\n      if (!face.image || face.image.isDisposedInternal) {\n        log('Face object is disposed:', face.image);\n        continue;\n      }\n\n      const angle = this.#calculateFaceAngle(face.mesh);\n\n      // run age, inherits face from blazeface\n      this.#analyze('Start Age:');\n      if (this.config.async) {\n        ageRes = this.config.face.age.enabled ? age.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:age';\n        timeStamp = now();\n        ageRes = this.config.face.age.enabled ? await age.predict(face.image, this.config) : {};\n        this.#perf.age = Math.trunc(now() - timeStamp);\n      }\n\n      // run gender, inherits face from blazeface\n      this.#analyze('Start Gender:');\n      if (this.config.async) {\n        genderRes = this.config.face.gender.enabled ? gender.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:gender';\n        timeStamp = now();\n        genderRes = this.config.face.gender.enabled ? await gender.predict(face.image, this.config) : {};\n        this.#perf.gender = Math.trunc(now() - timeStamp);\n      }\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Emotion:');\n      if (this.config.async) {\n        emotionRes = this.config.face.emotion.enabled ? emotion.predict(face.image, this.config) : {};\n      } else {\n        this.state = 'run:emotion';\n        timeStamp = now();\n        emotionRes = this.config.face.emotion.enabled ? await emotion.predict(face.image, this.config) : {};\n        this.#perf.emotion = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // run emotion, inherits face from blazeface\n      this.#analyze('Start Embedding:');\n      if (this.config.async) {\n        embeddingRes = this.config.face.embedding.enabled ? embedding.predict(face, this.config) : [];\n      } else {\n        this.state = 'run:embedding';\n        timeStamp = now();\n        embeddingRes = this.config.face.embedding.enabled ? await embedding.predict(face, this.config) : [];\n        this.#perf.embedding = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Emotion:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [ageRes, genderRes, emotionRes, embeddingRes] = await Promise.all([ageRes, genderRes, emotionRes, embeddingRes]);\n      }\n\n      this.#analyze('Finish Face:');\n\n      // calculate iris distance\n      // iris: array[ center, left, top, right, bottom]\n      if (!this.config.face.iris.enabled && face?.annotations?.leftEyeIris && face?.annotations?.rightEyeIris) {\n        delete face.annotations.leftEyeIris;\n        delete face.annotations.rightEyeIris;\n      }\n      const irisSize = (face.annotations?.leftEyeIris && face.annotations?.rightEyeIris)\n        /* average human iris size is 11.7mm */\n        ? 11.7 * Math.max(Math.abs(face.annotations.leftEyeIris[3][0] - face.annotations.leftEyeIris[1][0]), Math.abs(face.annotations.rightEyeIris[4][1] - face.annotations.rightEyeIris[2][1]))\n        : 0;\n\n      // combine results\n      faceRes.push({\n        ...face,\n        age: ageRes.age,\n        gender: genderRes.gender,\n        genderConfidence: genderRes.confidence,\n        emotion: emotionRes,\n        embedding: embeddingRes,\n        iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,\n        angle,\n        tensor: this.config.face.detector.return ? face.image?.squeeze() : null,\n      });\n      // dispose original face tensor\n      face.image?.dispose();\n\n      this.#analyze('End Face');\n    }\n    this.#analyze('End FaceMesh:');\n    if (this.config.async) {\n      if (this.#perf.face) delete this.#perf.face;\n      if (this.#perf.age) delete this.#perf.age;\n      if (this.#perf.gender) delete this.#perf.gender;\n      if (this.#perf.emotion) delete this.#perf.emotion;\n    }\n    return faceRes;\n  }\n\n  // main detect function\n  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {\n    // detection happens inside a promise\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig);\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        resolve({ error });\n      }\n\n      const timeStart = now();\n\n      // configure backend\n      await this.#checkBackend();\n\n      // load models if enabled\n      await this.load();\n\n      if (this.config.scoped) this.tf.engine().startScope();\n      this.#analyze('Start Scope:');\n\n      timeStamp = now();\n      const process = image.process(input, this.config);\n      if (!process || !process.tensor) {\n        log('could not convert input to tensor');\n        resolve({ error: 'could not convert input to tensor' });\n        return;\n      }\n      this.#perf.image = Math.trunc(now() - timeStamp);\n      this.#analyze('Get Image:');\n\n      // prepare where to store model results\n      let bodyRes;\n      let handRes;\n      let faceRes;\n      let objectRes;\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? this.#detectFace(process.tensor) : [];\n        if (this.#perf.face) delete this.#perf.face;\n      } else {\n        this.state = 'run:face';\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await this.#detectFace(process.tensor) : [];\n        this.#perf.face = Math.trunc(now() - timeStamp);\n      }\n\n      // run body: can be posenet or blazepose\n      this.#analyze('Start Body:');\n      if (this.config.async) {\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? blazepose.predict(process.tensor, this.config) : [];\n        if (this.#perf.body) delete this.#perf.body;\n      } else {\n        this.state = 'run:body';\n        timeStamp = now();\n        if (this.config.body.modelPath.includes('posenet')) bodyRes = this.config.body.enabled ? await this.models.posenet?.estimatePoses(process.tensor, this.config) : [];\n        else bodyRes = this.config.body.enabled ? await blazepose.predict(process.tensor, this.config) : [];\n        this.#perf.body = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Body:');\n\n      // run handpose\n      this.#analyze('Start Hand:');\n      if (this.config.async) {\n        handRes = this.config.hand.enabled ? this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        if (this.#perf.hand) delete this.#perf.hand;\n      } else {\n        this.state = 'run:hand';\n        timeStamp = now();\n        handRes = this.config.hand.enabled ? await this.models.handpose?.estimateHands(process.tensor, this.config) : [];\n        this.#perf.hand = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Hand:');\n\n      // run nanodet\n      this.#analyze('Start Object:');\n      if (this.config.async) {\n        objectRes = this.config.object.enabled ? nanodet.predict(process.tensor, this.config) : [];\n        if (this.#perf.object) delete this.#perf.object;\n      } else {\n        this.state = 'run:object';\n        timeStamp = now();\n        objectRes = this.config.object.enabled ? await nanodet.predict(process.tensor, this.config) : [];\n        this.#perf.object = Math.trunc(now() - timeStamp);\n      }\n      this.#analyze('End Object:');\n\n      // if async wait for results\n      if (this.config.async) {\n        [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n      }\n      process.tensor.dispose();\n\n      if (this.config.scoped) this.tf.engine().endScope();\n      this.#analyze('End Scope:');\n\n      let gestureRes = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        // @ts-ignore\n        gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];\n        if (!this.config.async) this.#perf.gesture = Math.trunc(now() - timeStamp);\n        else if (this.#perf.gesture) delete this.#perf.gesture;\n      }\n\n      this.#perf.total = Math.trunc(now() - timeStart);\n      this.state = 'idle';\n      const result = {\n        face: faceRes,\n        body: bodyRes,\n        hand: handRes,\n        gesture: gestureRes,\n        object: objectRes,\n        performance: this.#perf,\n        canvas: process.canvas,\n      };\n      // log('Result:', result);\n      resolve(result);\n    });\n  }\n\n  /** @hidden */\n  #warmupBitmap = async () => {\n    const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n    let blob;\n    let res;\n    switch (this.config.warmup) {\n      case 'face': blob = await b64toBlob(sample.face); break;\n      case 'full': blob = await b64toBlob(sample.body); break;\n      default: blob = null;\n    }\n    if (blob) {\n      const bitmap = await createImageBitmap(blob);\n      res = await this.detect(bitmap, this.config);\n      bitmap.close();\n    }\n    return res;\n  }\n\n  /** @hidden */\n  #warmupCanvas = async () => new Promise((resolve) => {\n    let src;\n    let size = 0;\n    switch (this.config.warmup) {\n      case 'face':\n        size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    const img = new Image();\n    img.onload = async () => {\n      const canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(size, size) : document.createElement('canvas');\n      canvas.width = img.naturalWidth;\n      canvas.height = img.naturalHeight;\n      const ctx = canvas.getContext('2d');\n      ctx?.drawImage(img, 0, 0);\n      // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n      const res = await this.detect(canvas, this.config);\n      resolve(res);\n    };\n    if (src) img.src = src;\n    else resolve(null);\n  });\n\n  /** @hidden */\n  #warmupNode = async () => {\n    const atob = (str) => Buffer.from(str, 'base64');\n    const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);\n    // @ts-ignore\n    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs\n    const expanded = data.expandDims(0);\n    this.tf.dispose(data);\n    // log('Input:', expanded);\n    const res = await this.detect(expanded, this.config);\n    this.tf.dispose(expanded);\n    return res;\n  }\n\n  async warmup(userConfig: Object = {}): Promise<Result | { error }> {\n    const t0 = now();\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    const save = this.config.videoOptimized;\n    this.config.videoOptimized = false;\n    let res;\n    if (typeof createImageBitmap === 'function') res = await this.#warmupBitmap();\n    else if (typeof Image !== 'undefined') res = await this.#warmupCanvas();\n    else res = await this.#warmupNode();\n    this.config.videoOptimized = save;\n    const t1 = now();\n    if (this.config.debug) log('Warmup', this.config.warmup, Math.round(t1 - t0), 'ms', res);\n    return res;\n  }\n}\n\nexport { Human as default };\n", "// helper function: wrapper around console output\nexport function log(...msg) {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n", "export function info() {\n  let platform;\n  let agent;\n  if (typeof navigator !== 'undefined') {\n    const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n    if (raw && raw[0]) {\n      // @ts-ignore\n      platform = raw[0].match(/\\(([^()]+)\\)/g)[0].replace(/\\(|\\)/g, '');\n      agent = navigator.userAgent.replace(raw[0], '');\n      if (platform[1]) agent = agent.replace(raw[1], '');\n      agent = agent.replace(/  /g, ' ');\n    }\n  } else if (typeof process !== 'undefined') {\n    platform = `${process.platform} ${process.arch}`;\n    agent = `NodeJS ${process.version}`;\n  }\n  return { platform, agent };\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nexport const config = {\n  name: 'humangl',\n  priority: 99,\n  canvas: null,\n  gl: null,\n  width: 1024,\n  height: 1024,\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nexport function register() {\n  if (!tf.findBackend(config.name)) {\n    log('backend registration:', config.name);\n    try {\n      // @ts-ignore\n      config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      // @ts-ignore\n      config.gl = config.canvas.getContext('webgl2', config.webGLattr);\n    } catch (err) {\n      log('error: cannot get WebGL2 context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL2 context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n      // @ts-ignore\n      // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));\n      // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    log('backend registered:', config.name);\n  }\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\n\nconst NUM_LANDMARKS = 6;\n\nfunction generateAnchors(inputSize) {\n  const spec = { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] };\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) {\n          anchors.push([anchorX, anchorY]);\n        }\n      }\n    }\n  }\n  return anchors;\n}\n\nexport const disposeBox = (box) => {\n  box.startEndTensor.dispose();\n  box.startPoint.dispose();\n  box.endPoint.dispose();\n};\n\nconst createBox = (startEndTensor) => ({\n  startEndTensor,\n  startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]),\n  endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]),\n});\n\nfunction decodeBounds(boxOutputs, anchors, inputSize) {\n  const boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  const centers = tf.add(boxStarts, anchors);\n  const boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  const boxSizesNormalized = tf.div(boxSizes, inputSize);\n  const centersNormalized = tf.div(centers, inputSize);\n  const halfBoxSize = tf.div(boxSizesNormalized, 2);\n  const starts = tf.sub(centersNormalized, halfBoxSize);\n  const ends = tf.add(centersNormalized, halfBoxSize);\n  const startNormalized = tf.mul(starts, inputSize);\n  const endNormalized = tf.mul(ends, inputSize);\n  const concatAxis = 1;\n  return tf.concat2d([startNormalized, endNormalized], concatAxis);\n}\n\nexport class BlazeFaceModel {\n  model: any;\n  anchorsData: any;\n  anchors: any;\n  inputSize: number;\n  config: any;\n\n  constructor(model, config) {\n    this.model = model;\n    this.anchorsData = generateAnchors(model.inputs[0].shape[1]);\n    this.anchors = tf.tensor2d(this.anchorsData);\n    this.inputSize = model.inputs[0].shape[2];\n    this.config = config;\n  }\n\n  async getBoundingBoxes(inputImage) {\n    // sanity check on input\n    if ((!inputImage) || (inputImage.isDisposedInternal) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return null;\n    const [batch, boxes, scores] = tf.tidy(() => {\n      const resizedImage = inputImage.resizeBilinear([this.inputSize, this.inputSize]);\n      // const normalizedImage = tf.mul(tf.sub(resizedImage.div(255), 0.5), 2);\n      const normalizedImage = resizedImage.div(127.5).sub(0.5);\n      const batchedPrediction = this.model.predict(normalizedImage);\n      let batchOut;\n      // are we using tfhub or pinto converted model?\n      if (Array.isArray(batchedPrediction)) {\n        const sorted = batchedPrediction.sort((a, b) => a.size - b.size);\n        const concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n        const concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n        const concat = tf.concat([concat512, concat384], 1);\n        batchOut = concat.squeeze(0);\n      } else {\n        batchOut = batchedPrediction.squeeze(); // when using tfhub model\n      }\n      const boxesOut = decodeBounds(batchOut, this.anchors, [this.inputSize, this.inputSize]);\n      const logits = tf.slice(batchOut, [0, 0], [-1, 1]);\n      const scoresOut = tf.sigmoid(logits).squeeze();\n      return [batchOut, boxesOut, scoresOut];\n    });\n    const boxIndicesTensor = await tf.image.nonMaxSuppressionAsync(boxes, scores, this.config.face.detector.maxFaces, this.config.face.detector.iouThreshold, this.config.face.detector.scoreThreshold);\n    const boxIndices = boxIndicesTensor.arraySync();\n    boxIndicesTensor.dispose();\n    const boundingBoxesMap = boxIndices.map((boxIndex) => tf.slice(boxes, [boxIndex, 0], [1, -1]));\n    const boundingBoxes = boundingBoxesMap.map((boundingBox) => {\n      const vals = boundingBox.arraySync();\n      boundingBox.dispose();\n      return vals;\n    });\n\n    const scoresVal = scores.dataSync();\n    const annotatedBoxes: Array<{ box: any, landmarks: any, anchor: any, confidence: number }> = [];\n    for (let i = 0; i < boundingBoxes.length; i++) {\n      const boxIndex = boxIndices[i];\n      const confidence = scoresVal[boxIndex];\n      if (confidence > this.config.face.detector.minConfidence) {\n        const box = createBox(boundingBoxes[i]);\n        const anchor = this.anchorsData[boxIndex];\n        const landmarks = tf.tidy(() => tf.slice(batch, [boxIndex, NUM_LANDMARKS - 1], [1, -1]).squeeze().reshape([NUM_LANDMARKS, -1]));\n        annotatedBoxes.push({ box, landmarks, anchor, confidence });\n      }\n    }\n    batch.dispose();\n    boxes.dispose();\n    scores.dispose();\n    return {\n      boxes: annotatedBoxes,\n      scaleFactor: [inputImage.shape[2] / this.inputSize, inputImage.shape[1] / this.inputSize],\n    };\n  }\n}\n\nexport async function load(config) {\n  const blazeface = await tf.loadGraphModel(config.face.detector.modelPath, { fromTFHub: config.face.detector.modelPath.includes('tfhub.dev') });\n  const model = new BlazeFaceModel(blazeface, config);\n  if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return model;\n}\n", "/* eslint-disable class-methods-use-this */\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as bounding from './box';\nimport * as util from './util';\nimport * as coords from './coords';\n\nconst leftOutline = coords.MESH_ANNOTATIONS['leftEyeLower0'];\nconst rightOutline = coords.MESH_ANNOTATIONS['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst meshLandmarks = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, coords.MESH_ANNOTATIONS['midwayBetweenEyes'][0]],\n};\n\nconst blazeFaceLandmarks = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates\n// Update the z coordinate to be an average of the original and the new.\nfunction replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {\n    const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];\n    const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];\n    // @ts-ignore\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0], newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n// The Pipeline coordinates between the bounding box and skeleton models.\nexport class Pipeline {\n  storedBoxes: any;\n  boundingBoxDetector: any;\n  meshDetector: any;\n  irisModel: any;\n  boxSize: number;\n  meshSize: number;\n  irisSize: number;\n  irisEnlarge: number;\n  skipped: number;\n  detectedFaces: number;\n\n  constructor(boundingBoxDetector, meshDetector, irisModel) {\n    // An array of facial bounding boxes.\n    this.storedBoxes = [];\n    this.boundingBoxDetector = boundingBoxDetector;\n    this.meshDetector = meshDetector;\n    this.irisModel = irisModel;\n    this.boxSize = boundingBoxDetector?.model?.inputs[0].shape[2] || 0;\n    this.meshSize = meshDetector?.inputs[0].shape[2] || boundingBoxDetector?.model?.inputs[0].shape[2];\n    this.irisSize = irisModel?.inputs[0].shape[1] || 0;\n    this.irisEnlarge = 2.3;\n    this.skipped = 0;\n    this.detectedFaces = 0;\n  }\n\n  transformRawCoords(rawCoords, box, angle, rotationMatrix) {\n    const boxSize = bounding.getBoxSize({ startPoint: box.startPoint, endPoint: box.endPoint });\n    const coordsScaled = rawCoords.map((coord) => ([\n      boxSize[0] / this.meshSize * (coord[0] - this.meshSize / 2),\n      boxSize[1] / this.meshSize * (coord[1] - this.meshSize / 2),\n      coord[2],\n    ]));\n    const coordsRotationMatrix = (angle !== 0) ? util.buildRotationMatrix(angle, [0, 0]) : util.IDENTITY_MATRIX;\n    const coordsRotated = (angle !== 0) ? coordsScaled.map((coord) => ([...util.rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n    const inverseRotationMatrix = (angle !== 0) ? util.invertTransformMatrix(rotationMatrix) : util.IDENTITY_MATRIX;\n    const boxCenter = [...bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint }), 1];\n    return coordsRotated.map((coord) => ([\n      coord[0] + util.dot(boxCenter, inverseRotationMatrix[0]),\n      coord[1] + util.dot(boxCenter, inverseRotationMatrix[1]),\n      coord[2],\n    ]));\n  }\n\n  getLeftToRightEyeDepthDifference(rawCoords) {\n    const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n    const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n    return leftEyeZ - rightEyeZ;\n  }\n\n  // Returns a box describing a cropped region around the eye fit for passing to the iris model.\n  getEyeBox(rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, flip = false) {\n    const box = bounding.squarifyBox(bounding.enlargeBox(this.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), this.irisEnlarge));\n    const boxSize = bounding.getBoxSize(box);\n    let crop = tf.image.cropAndResize(face, [[\n      box.startPoint[1] / this.meshSize,\n      box.startPoint[0] / this.meshSize, box.endPoint[1] / this.meshSize,\n      box.endPoint[0] / this.meshSize,\n    ]], [0], [this.irisSize, this.irisSize]);\n    if (flip && tf.ENV.flags.IS_BROWSER) {\n      crop = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    }\n    return { box, boxSize, crop };\n  }\n\n  // Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\n  getEyeCoords(eyeData, eyeBox, eyeBoxSize, flip = false) {\n    const eyeRawCoords: Array<any[]> = [];\n    for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n      const x = eyeData[i * 3];\n      const y = eyeData[i * 3 + 1];\n      const z = eyeData[i * 3 + 2];\n      eyeRawCoords.push([\n        (flip ? (1 - (x / this.irisSize)) : (x / this.irisSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n        (y / this.irisSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n      ]);\n    }\n    return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n  }\n\n  // The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\n  getAdjustedIrisCoords(rawCoords, irisCoords, direction) {\n    const upperCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n    const lowerCenterZ = rawCoords[coords.MESH_ANNOTATIONS[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n    const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n    // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n    return irisCoords.map((coord, i) => {\n      let z = averageZ;\n      if (i === 2) {\n        z = upperCenterZ;\n      } else if (i === 4) {\n        z = lowerCenterZ;\n      }\n      return [coord[0], coord[1], z];\n    });\n  }\n\n  async predict(input, config) {\n    let useFreshBox = false;\n    // run new detector every skipFrames unless we only want box to start with\n    let detector;\n    if ((this.skipped === 0) || (this.skipped > config.face.detector.skipFrames) || !config.face.mesh.enabled || !config.videoOptimized) {\n      detector = await this.boundingBoxDetector.getBoundingBoxes(input);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (detector && detector.boxes && (!config.face.mesh.enabled || (detector.boxes.length !== this.detectedFaces) && (this.detectedFaces !== config.face.detector.maxFaces))) {\n      this.storedBoxes = [];\n      this.detectedFaces = 0;\n      for (const possible of detector.boxes) {\n        this.storedBoxes.push({ startPoint: possible.box.startPoint.dataSync(), endPoint: possible.box.endPoint.dataSync(), landmarks: possible.landmarks, confidence: possible.confidence });\n      }\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n\n    if (config.face.detector.skipInitial && this.detectedFaces === 0) this.skipped = 0;\n\n    if (useFreshBox) {\n      if (!detector || !detector.boxes || (detector.boxes.length === 0)) {\n        this.storedBoxes = [];\n        this.detectedFaces = 0;\n        return null;\n      }\n      for (let i = 0; i < this.storedBoxes.length; i++) {\n        const scaledBox = bounding.scaleBoxCoordinates({ startPoint: this.storedBoxes[i].startPoint, endPoint: this.storedBoxes[i].endPoint }, detector.scaleFactor);\n        const enlargedBox = bounding.enlargeBox(scaledBox);\n        const squarifiedBox = bounding.squarifyBox(enlargedBox);\n        const landmarks = this.storedBoxes[i].landmarks.arraySync();\n        const confidence = this.storedBoxes[i].confidence;\n        this.storedBoxes[i] = { ...squarifiedBox, confidence, landmarks };\n      }\n    }\n    if (detector && detector.boxes) {\n      detector.boxes.forEach((prediction) => {\n        prediction.box.startPoint.dispose();\n        prediction.box.endPoint.dispose();\n        prediction.landmarks.dispose();\n      });\n    }\n\n    let results = tf.tidy(() => this.storedBoxes.map((box, i) => {\n      const boxConfidence = box.confidence;\n\n      // The facial bounding box landmarks could come either from blazeface (if we are using a fresh box), or from the mesh model (if we are reusing an old box).\n      let face;\n      let angle = 0;\n      let rotationMatrix;\n\n      if (config.face.detector.rotation && config.face.mesh.enabled && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.boxSize, this.boxSize]).div(255);\n      } else {\n        rotationMatrix = util.IDENTITY_MATRIX;\n        const clonedImage = input.clone();\n        if (config.face.mesh.enabled) face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.meshSize, this.meshSize]).div(255);\n        else face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, clonedImage, [this.boxSize, this.boxSize]).div(255);\n      }\n\n      // if we're not going to produce mesh, don't spend time with further processing\n      if (!config.face.mesh.enabled) {\n        const prediction = {\n          coords: null,\n          box,\n          faceConfidence: null,\n          boxConfidence: box.confidence,\n          confidence: box.confidence,\n          image: face,\n        };\n        return prediction;\n      }\n\n      const [, confidence, contourCoords] = this.meshDetector.predict(face); // The first returned tensor represents facial contours which are already included in the coordinates.\n      const faceConfidence = confidence.dataSync()[0];\n      if (faceConfidence < config.face.detector.minConfidence) return null; // if below confidence just exit\n      const coordsReshaped = tf.reshape(contourCoords, [-1, 3]);\n      let rawCoords = coordsReshaped.arraySync();\n\n      if (config.face.iris.enabled) {\n        const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], true);\n        const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = this.getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1]);\n        const eyePredictions = this.irisModel.predict(tf.concat([leftEyeCrop, rightEyeCrop]));\n        const eyePredictionsData = eyePredictions.dataSync();\n        const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n        const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = this.getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n        const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n        const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = this.getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize);\n        const leftToRightEyeDepthDifference = this.getLeftToRightEyeDepthDifference(rawCoords);\n        if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', null);\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', null);\n          // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged\n          // So we only update a single contour line above and below the eye.\n        } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n          replaceRawCoordinates(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n        } else { // User is looking towards the left.\n          replaceRawCoordinates(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n        }\n        const adjustedLeftIrisCoords = this.getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n        const adjustedRightIrisCoords = this.getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n        rawCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n      }\n\n      // override box from detection with one calculated from mesh\n      const transformedCoordsData = this.transformRawCoords(rawCoords, box, angle, rotationMatrix);\n      box = bounding.enlargeBox(this.calculateLandmarksBoundingBox(transformedCoordsData), 1.5); // redefine box with mesh calculated one\n      const transformedCoords = tf.tensor2d(transformedCoordsData);\n\n      // do rotation one more time with mesh keypoints if we want to return perfect image\n      if (config.face.detector.rotation && config.face.mesh.enabled && config.face.detector.return && tf.ENV.flags.IS_BROWSER) {\n        const [indexOfMouth, indexOfForehead] = (box.landmarks.length >= meshLandmarks.count) ? meshLandmarks.symmetryLine : blazeFaceLandmarks.symmetryLine;\n        angle = util.computeRotation(box.landmarks[indexOfMouth], box.landmarks[indexOfForehead]);\n        const faceCenter = bounding.getBoxCenter({ startPoint: box.startPoint, endPoint: box.endPoint });\n        const faceCenterNormalized = [faceCenter[0] / input.shape[2], faceCenter[1] / input.shape[1]];\n        const rotatedImage = tf.image.rotateWithOffset(input, angle, 0, faceCenterNormalized); // rotateWithOffset is not defined for tfjs-node\n        rotationMatrix = util.buildRotationMatrix(-angle, faceCenter);\n        face = bounding.cutBoxFromImageAndResize({ startPoint: box.startPoint, endPoint: box.endPoint }, rotatedImage, [this.meshSize, this.meshSize]).div(255);\n      }\n\n      const prediction = {\n        coords: transformedCoords,\n        box,\n        faceConfidence,\n        boxConfidence,\n        image: face,\n        rawCoords,\n      };\n\n      // updated stored cache values\n      const squarifiedLandmarksBox = bounding.squarifyBox(box);\n      this.storedBoxes[i] = { ...squarifiedLandmarksBox, landmarks: transformedCoordsData, confidence: box.confidence, faceConfidence };\n\n      return prediction;\n    }));\n\n    results = results.filter((a) => a !== null);\n    // remove cache entries for detected boxes on low confidence\n    if (config.face.mesh.enabled) this.storedBoxes = this.storedBoxes.filter((a) => a.faceConfidence > config.face.detector.minConfidence);\n    this.detectedFaces = results.length;\n\n    return results;\n  }\n\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint, landmarks };\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint };\n}\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, landmarks: box.landmarks };\n}\n", "export const IDENTITY_MATRIX = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n/**\n * Normalizes the provided angle to the range -pi to pi.\n * @param angle The angle in radians to be normalized.\n */\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\n/**\n * Computes the angle of rotation between two anchor points.\n * @param point1 First anchor point\n * @param point2 Second anchor point\n */\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport function radToDegrees(rad) {\n  return rad * 180 / Math.PI;\n}\n\nexport function buildTranslationMatrix(x, y) {\n  return [[1, 0, x], [0, 1, y], [0, 0, 1]];\n}\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n\nexport function xyDistanceBetweenPoints(a, b) {\n  return Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n}\n", "export const MESH_ANNOTATIONS = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291],\n  lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173],\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133],\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190],\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243],\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189],\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244],\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245],\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193],\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65],\n  rightEyeIris: [473, 474, 475, 476, 477],\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const MESH_TO_IRIS_INDICES_MAP = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] },\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] },\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] },\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] },\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] },\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] },\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] },\n  // { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] },\n  // { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] },\n];\n\nexport const UV468 = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 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0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468 = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68 = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33 = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7 = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68 = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33 = [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];\n\nexport const VTX7 = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { age: 0 };\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.age.modelPath);\n    if (config.debug) log(`load model: ${config.face.age.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.age.skipFrames) && config.videoOptimized && last.age && (last.age > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const enhance = tf.mul(resize, [255.0]);\n    tf.dispose(resize);\n\n    let ageT;\n    const obj = { age: 0 };\n\n    if (!config.profile) {\n      if (config.face.age.enabled) ageT = await model.predict(enhance);\n    } else {\n      const profileAge = config.face.age.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      ageT = profileAge.result.clone();\n      profileAge.result.dispose();\n      profile.run('age', profileAge);\n    }\n    enhance.dispose();\n\n    if (ageT) {\n      const data = ageT.dataSync();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    ageT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from './log';\n\nexport const data = {};\n\nexport function run(name: string, raw: any) {\n  if (!raw || !raw.kernels) return;\n  const maxResults = 5;\n  const time = raw.kernels\n    .filter((a) => a.kernelTimeMs > 0)\n    .reduce((a, b) => a += b.kernelTimeMs, 0);\n  const slowest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.kernelTimeMs > 0)\n    .sort((a, b) => b.kernelTimeMs - a.kernelTimeMs);\n  const largest = raw.kernels\n    .map((a, i) => { a.id = i; return a; })\n    .filter((a) => a.totalBytesSnapshot > 0)\n    .sort((a, b) => b.totalBytesSnapshot - a.totalBytesSnapshot);\n  if (slowest.length > maxResults) slowest.length = maxResults;\n  if (largest.length > maxResults) largest.length = maxResults;\n  const res = { newBytes: raw.newBytes, newTensors: raw.newTensors, peakBytes: raw.peakBytes, numKernelOps: raw.kernels.length, timeKernelOps: time, slowestKernelOps: slowest, largestKernelOps: largest };\n  data[name] = res;\n  log('Human profiler', name, res);\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last = { gender: '' };\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet alternative = false;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.gender.modelPath);\n    alternative = model.inputs[0].shape[3] === 1;\n    if (config.debug) log(`load model: ${config.face.gender.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.gender.skipFrames) && config.videoOptimized && last.gender !== '') {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    let enhance;\n    if (alternative) {\n      enhance = tf.tidy(() => {\n        const [red, green, blue] = tf.split(resize, 3, 3);\n        const redNorm = tf.mul(red, rgb[0]);\n        const greenNorm = tf.mul(green, rgb[1]);\n        const blueNorm = tf.mul(blue, rgb[2]);\n        const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n        const normalize = grayscale.sub(0.5).mul(2); // range grayscale:-1..1\n        return normalize;\n      });\n    } else {\n      enhance = tf.mul(resize, [255.0]); // range RGB:0..255\n    }\n    tf.dispose(resize);\n\n    let genderT;\n    const obj = { gender: '', confidence: 0 };\n\n    if (!config.profile) {\n      if (config.face.gender.enabled) genderT = await model.predict(enhance);\n    } else {\n      const profileGender = config.face.gender.enabled ? await tf.profile(() => model.predict(enhance)) : {};\n      genderT = profileGender.result.clone();\n      profileGender.result.dispose();\n      profile.run('gender', profileGender);\n    }\n    enhance.dispose();\n\n    if (genderT) {\n      const data = genderT.dataSync();\n      if (alternative) {\n        // returns two values 0..1, bigger one is prediction\n        if (data[0] > config.face.gender.minConfidence || data[1] > config.face.gender.minConfidence) {\n          obj.gender = data[0] > data[1] ? 'female' : 'male';\n          obj.confidence = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n        }\n      } else {\n        // returns one value 0..1, .5 is prediction threshold\n        const confidence = Math.trunc(200 * Math.abs((data[0] - 0.5))) / 100;\n        if (confidence > config.face.gender.minConfidence) {\n          obj.gender = data[0] <= 0.5 ? 'female' : 'male';\n          obj.confidence = Math.min(0.99, confidence);\n        }\n      }\n    }\n    genderT.dispose();\n\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model;\nlet last: Array<{ score: number, emotion: string }> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.emotion.modelPath);\n    if (config.debug) log(`load model: ${config.face.emotion.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if ((skipped < config.face.emotion.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    const [red, green, blue] = tf.split(resize, 3, 3);\n    resize.dispose();\n    // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    red.dispose();\n    green.dispose();\n    blue.dispose();\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    redNorm.dispose();\n    greenNorm.dispose();\n    blueNorm.dispose();\n    const normalize = tf.tidy(() => grayscale.sub(0.5).mul(2));\n    grayscale.dispose();\n    const obj: Array<{ score: number, emotion: string }> = [];\n    if (config.face.emotion.enabled) {\n      let data;\n      if (!config.profile) {\n        const emotionT = await model.predict(normalize); // result is already in range 0..1, no need for additional activation\n        data = emotionT.dataSync();\n        tf.dispose(emotionT);\n      } else {\n        const profileData = await tf.profile(() => model.predict(normalize));\n        data = profileData.result.dataSync();\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > config.face.emotion.minConfidence) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] });\n      }\n      obj.sort((a, b) => b.score - a.score);\n    }\n    normalize.dispose();\n    last = obj;\n    resolve(obj);\n  });\n}\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\ntype Tensor = {};\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.face.embedding.modelPath);\n    if (config.debug) log(`load model: ${config.face.embedding.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport function simmilarity(embedding1, embedding2, order = 2): Number {\n  if (!embedding1 || !embedding2) return 0;\n  if (embedding1?.length === 0 || embedding2?.length === 0) return 0;\n  if (embedding1?.length !== embedding2?.length) return 0;\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  const distance = embedding1\n    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared\n    .reduce((sum, now) => (sum + now), 0) // sum all distances\n    ** (1 / order); // get root of\n  const res = Math.max(Math.trunc(1000 * (1 - distance)) / 1000, 0);\n  return res;\n}\n\nexport function match(embedding: Array<Number>, db: Array<any>, threshold = 0) {\n  let best = { simmilarity: 0, name: '', source: '', embedding: [] };\n  if (!embedding || !db || !Array.isArray(embedding) || !Array.isArray(db)) return best;\n  for (const f of db) {\n    if (f.embedding && f.name) {\n      const perc = simmilarity(embedding, f.embedding);\n      if (perc > threshold && perc > best.simmilarity) best = { ...f, simmilarity: perc };\n    }\n  }\n  return best;\n}\n\nexport function enhance(input): Tensor {\n  const image = tf.tidy(() => {\n    // input received from detector is already normalized to 0..1\n    // input is also assumed to be straightened\n    // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n    // do a tight crop of image and resize it to fit the model\n    const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n    const tensor = input.image || input.tensor;\n    if (!(tensor instanceof tf.Tensor)) return null;\n    const crop = (tensor.shape.length === 3)\n      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n      : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n\n    // convert to black&white to avoid colorization impact\n    const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n    const [red, green, blue] = tf.split(crop, 3, 3);\n    const redNorm = tf.mul(red, rgb[0]);\n    const greenNorm = tf.mul(green, rgb[1]);\n    const blueNorm = tf.mul(blue, rgb[2]);\n    const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n    const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n    /*\n    // optional increase image contrast\n    // or do it per-channel so mean is done on each channel\n    // or do it based on histogram\n    const mean = merge.mean();\n    const factor = 5;\n    const contrast = merge.sub(mean).mul(factor).add(mean);\n    */\n\n    // normalize brightness from 0..1\n    const darken = merge.sub(merge.min());\n    const lighten = darken.div(darken.max());\n\n    return lighten;\n  });\n  return image;\n}\n\nexport async function predict(input, config): Promise<number[]> {\n  if (!model) return [];\n  return new Promise(async (resolve) => {\n    // let data: Array<[]> = [];\n    let data: Array<number> = [];\n    if (config.face.embedding.enabled) {\n      const image = enhance(input);\n      if (!config.profile) {\n        data = tf.tidy(() => {\n          /*\n          // if needed convert from NHWC to NCHW\n          const nchw = image.transpose([3, 0, 1, 2]);\n          */\n\n          const res = model.predict(image);\n\n          /*\n          // optionally do it twice with flipped image and average results\n          const res1 = model.predict(image);\n          const flipped = tf.image.flipLeftRight(image);\n          const res2 = model.predict(flipped);\n          const merge = tf.stack([res1, res2], 2).squeeze();\n          const res = reshape.logSumExp(1);\n          */\n\n          /*\n          // optional normalize outputs with l2 normalization\n          const scaled = tf.tidy(() => {\n            const l2 = res.norm('euclidean');\n            const scale = res.div(l2);\n            return scale;\n          });\n          */\n\n          // optional reduce feature vector complexity\n          const reshape = res.reshape([128, 2]); // split 256 vectors into 128 x 2\n          const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n\n          const output: Array<number> = reduce.dataSync();\n          return [...output]; // convert typed array to simple array\n        });\n      } else {\n        const profileData = await tf.profile(() => model.predict({ img_inputs: image }));\n        data = [...profileData.result.dataSync()];\n        profileData.result.dispose();\n        profile.run('emotion', profileData);\n      }\n      tf.dispose(image);\n    }\n    resolve(data);\n  });\n}\n\n/*\ngit clone https://github.com/becauseofAI/MobileFace\ncd MobileFace/MobileFace_Identification\nmmconvert --srcFramework mxnet --inputWeight MobileFace_Identification_V3-0000.params --inputNetwork MobileFace_Identification_V3-symbol.json --inputShape 3,112,112 --dstFramework tensorflow --outputModel saved\nsaved_model_cli show --dir saved/\ntensorflowjs_converter --input_format tf_saved_model --output_format tfjs_graph_model --saved_model_tags train saved/ graph/\n~/dev/detector/signature.js graph/\n2021-03-12 08:25:12 DATA:  created on: 2021-03-12T13:17:11.960Z\n2021-03-12 08:25:12 INFO:  graph model: /home/vlado/dev/face/MobileFace/MobileFace_Identification/graph/model.json\n2021-03-12 08:25:12 INFO:  size: { unreliable: true, numTensors: 75, numDataBuffers: 75, numBytes: 2183192 }\n2021-03-12 08:25:12 INFO:  model inputs based on signature\n2021-03-12 08:25:12 INFO:  model outputs based on signature\n2021-03-12 08:25:12 DATA:  inputs: [ { name: 'data:0', dtype: 'DT_FLOAT', shape: [ -1, 112, 112, 3, [length]: 4 ] }, [length]: 1 ]\n2021-03-12 08:25:12 DATA:  outputs: [ { id: 0, name: 'batchnorm0/add_1:0', dytpe: 'DT_FLOAT', shape: [ -1, 256, [length]: 2 ] }, [length]: 1 ]\n*/\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as modelBase from './modelBase';\nimport * as decodeMultiple from './decodeMultiple';\nimport * as decodePose from './decodePose';\nimport * as util from './util';\n\nasync function estimateMultiple(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const allTensorBuffers = await util.toTensorBuffers3D([res.heatmapScores, res.offsets, res.displacementFwd, res.displacementBwd]);\n    const scoresBuffer = allTensorBuffers[0];\n    const offsetsBuffer = allTensorBuffers[1];\n    const displacementsFwdBuffer = allTensorBuffers[2];\n    const displacementsBwdBuffer = allTensorBuffers[3];\n    const poses = await decodeMultiple.decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, config.body.nmsRadius, config.body.maxDetections, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses(poses, [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nasync function estimateSingle(input, res, config, inputSize) {\n  return new Promise(async (resolve) => {\n    const pose = await decodePose.decodeSinglePose(res.heatmapScores, res.offsets, config.body.scoreThreshold);\n    const scaled = util.scaleAndFlipPoses([pose], [input.shape[1], input.shape[2]], [inputSize, inputSize]);\n    resolve(scaled);\n  });\n}\n\nexport class PoseNet {\n  baseModel: any;\n  inputSize: number\n  constructor(model) {\n    this.baseModel = model;\n    this.inputSize = model.model.inputs[0].shape[1];\n    if (this.inputSize < 128) this.inputSize = 257;\n  }\n\n  async estimatePoses(input, config) {\n    const resized = util.resizeTo(input, [this.inputSize, this.inputSize]);\n    const res = this.baseModel.predict(resized, config);\n\n    const poses = (config.body.maxDetections < 2)\n      ? await estimateSingle(input, res, config, this.inputSize)\n      : await estimateMultiple(input, res, config, this.inputSize);\n\n    res.heatmapScores.dispose();\n    res.offsets.dispose();\n    res.displacementFwd.dispose();\n    res.displacementBwd.dispose();\n    resized.dispose();\n\n    return poses;\n  }\n\n  dispose() {\n    this.baseModel.dispose();\n  }\n}\n\nexport async function load(config) {\n  const model = await tf.loadGraphModel(config.body.modelPath);\n  const mobilenet = new modelBase.BaseModel(model);\n  if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return new PoseNet(mobilenet);\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nfunction nameOutputResultsMobileNet(results) {\n  const [offsets, heatmap, displacementFwd, displacementBwd] = results;\n  return { offsets, heatmap, displacementFwd, displacementBwd };\n}\n\nexport class BaseModel {\n  model: any;\n  constructor(model) {\n    this.model = model;\n  }\n\n  predict(input) {\n    return tf.tidy(() => {\n      const asFloat = input.toFloat().div(127.5).sub(1.0);\n      const asBatch = asFloat.expandDims(0);\n      const results = this.model.predict(asBatch);\n      const results3d = results.map((y) => y.squeeze([0]));\n      const namedResults = nameOutputResultsMobileNet(results3d);\n      return {\n        heatmapScores: namedResults.heatmap.sigmoid(),\n        offsets: namedResults.offsets,\n        displacementFwd: namedResults.displacementFwd,\n        displacementBwd: namedResults.displacementBwd,\n      };\n    });\n  }\n\n  dispose() {\n    this.model.dispose();\n  }\n}\n", "// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nfunction half(k) {\n  return Math.floor(k / 2);\n}\nexport class MaxHeap {\n  priorityQueue: any;\n  numberOfElements: number;\n  getElementValue: any;\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() {\n    return this.numberOfElements === -1;\n  }\n\n  size() {\n    return this.numberOfElements + 1;\n  }\n\n  all() {\n    return this.priorityQueue.slice(0, this.numberOfElements + 1);\n  }\n\n  max() {\n    return this.priorityQueue[0];\n  }\n\n  swim(k) {\n    while (k > 0 && this.less(half(k), k)) {\n      this.exchange(k, half(k));\n      k = half(k);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n", "import * as heapSort from './heapSort';\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(scoreThreshold, localMaximumRadius, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new heapSort.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < scoreThreshold) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, localMaximumRadius, scores)) {\n          queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n        }\n      }\n    }\n  }\n  return queue;\n}\n", "import * as keypoints from './keypoints';\nimport * as vectors from './vectors';\nimport * as decoders from './decoders';\n\nconst parentChildrenTuples = keypoints.poseChain.map(([parentJoinName, childJoinName]) => ([keypoints.partIds[parentJoinName], keypoints.partIds[childJoinName]]));\nconst parentToChildEdges = parentChildrenTuples.map(([, childJointId]) => childJointId);\nconst childToParentEdges = parentChildrenTuples.map(([parentJointId]) => parentJointId);\n\nconst defaultOutputStride = 16;\n\nfunction getDisplacement(edgeId, point, displacements) {\n  const numEdges = displacements.shape[2] / 2;\n  return {\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, numEdges + edgeId),\n  };\n}\n\nfunction getStridedIndexNearPoint(point, outputStride, height, width) {\n  return {\n    y: vectors.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: vectors.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  };\n}\n\nfunction traverseToTargetKeypoint(edgeId, sourceKeypoint, targetKeypointId, scoresBuffer, offsets, outputStride, displacements, offsetRefineStep = 2) {\n  const [height, width] = scoresBuffer.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, outputStride, height, width);\n  const displacement = getDisplacement(edgeId, sourceKeypointIndices, displacements);\n  const displacedPoint = vectors.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n    const offsetPoint = vectors.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetKeypointId, offsets);\n    targetKeypoint = vectors.addVectors({\n      x: targetKeypointIndices.x * outputStride,\n      y: targetKeypointIndices.y * outputStride,\n    }, { x: offsetPoint.x, y: offsetPoint.y });\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, outputStride, height, width);\n  const score = scoresBuffer.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetKeypointId);\n  return { position: targetKeypoint, part: keypoints.partNames[targetKeypointId], score };\n}\n\nexport function decodePose(root, scores, offsets, outputStride, displacementsFwd, displacementsBwd) {\n  const numParts = scores.shape[2];\n  const numEdges = parentToChildEdges.length;\n  const instanceKeypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const { part: rootPart, score: rootScore } = root;\n  const rootPoint = vectors.getImageCoords(rootPart, outputStride, offsets);\n  instanceKeypoints[rootPart.id] = {\n    score: rootScore,\n    part: keypoints.partNames[rootPart.id],\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceKeypointId = parentToChildEdges[edge];\n    const targetKeypointId = childToParentEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceKeypointId = childToParentEdges[edge];\n    const targetKeypointId = parentToChildEdges[edge];\n    if (instanceKeypoints[sourceKeypointId] && !instanceKeypoints[targetKeypointId]) {\n      instanceKeypoints[targetKeypointId] = traverseToTargetKeypoint(edge, instanceKeypoints[sourceKeypointId], targetKeypointId, scores, offsets, outputStride, displacementsFwd);\n    }\n  }\n  return instanceKeypoints;\n}\n\nexport async function decodeSinglePose(heatmapScores, offsets, minScore) {\n  let totalScore = 0.0;\n  const heatmapValues = decoders.argmax2d(heatmapScores);\n  const allTensorBuffers = await Promise.all([heatmapScores.buffer(), offsets.buffer(), heatmapValues.buffer()]);\n  const scoresBuffer = allTensorBuffers[0];\n  const offsetsBuffer = allTensorBuffers[1];\n  const heatmapValuesBuffer = allTensorBuffers[2];\n  const offsetPoints = decoders.getOffsetPoints(heatmapValuesBuffer, defaultOutputStride, offsetsBuffer);\n  const offsetPointsBuffer = await offsetPoints.buffer();\n  const keypointConfidence = Array.from(decoders.getPointsConfidence(scoresBuffer, heatmapValuesBuffer));\n  const instanceKeypoints = keypointConfidence.map((score, i) => {\n    totalScore += score;\n    return {\n      position: {\n        y: offsetPointsBuffer.get(i, 0),\n        x: offsetPointsBuffer.get(i, 1),\n      },\n      part: keypoints.partNames[i],\n      score,\n    };\n  });\n  const filteredKeypoints = instanceKeypoints.filter((kpt) => kpt.score > minScore);\n  heatmapValues.dispose();\n  offsetPoints.dispose();\n  return { keypoints: filteredKeypoints, score: totalScore / instanceKeypoints.length };\n}\n", "import * as kpt from './keypoints';\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as kpt from './keypoints';\n\nexport function getPointsConfidence(heatmapScores, heatMapCoords) {\n  const numKeypoints = heatMapCoords.shape[0];\n  const result = new Float32Array(numKeypoints);\n  for (let keypoint = 0; keypoint < numKeypoints; keypoint++) {\n    const y = heatMapCoords.get(keypoint, 0);\n    const x = heatMapCoords.get(keypoint, 1);\n    result[keypoint] = heatmapScores.get(y, x, keypoint);\n  }\n  return result;\n}\n\nfunction getOffsetPoint(y, x, keypoint, offsetsBuffer) {\n  return {\n    y: offsetsBuffer.get(y, x, keypoint),\n    x: offsetsBuffer.get(y, x, keypoint + kpt.NUM_KEYPOINTS),\n  };\n}\n\nexport function getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer) {\n  const result: Array<number> = [];\n  for (let keypoint = 0; keypoint < kpt.NUM_KEYPOINTS; keypoint++) {\n    const heatmapY = heatMapCoordsBuffer.get(keypoint, 0).valueOf();\n    const heatmapX = heatMapCoordsBuffer.get(keypoint, 1).valueOf();\n    const { x, y } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsetsBuffer);\n    result.push(y);\n    result.push(x);\n  }\n  return tf.tensor2d(result, [kpt.NUM_KEYPOINTS, 2]);\n}\n\nexport function getOffsetPoints(heatMapCoordsBuffer, outputStride, offsetsBuffer) {\n  return tf.tidy(() => heatMapCoordsBuffer.toTensor().mul(tf.scalar(outputStride, 'int32')).toFloat().add(getOffsetVectors(heatMapCoordsBuffer, offsetsBuffer)));\n}\n\nfunction mod(a, b) {\n  return tf.tidy(() => {\n    const floored = a.div(tf.scalar(b, 'int32'));\n    return a.sub(floored.mul(tf.scalar(b, 'int32')));\n  });\n}\n\nexport function argmax2d(inputs) {\n  const [height, width, depth] = inputs.shape;\n  return tf.tidy(() => {\n    const reshaped = inputs.reshape([height * width, depth]);\n    const coords = reshaped.argMax(0);\n    const yCoords = coords.div(tf.scalar(width, 'int32')).expandDims(1);\n    const xCoords = mod(coords, width).expandDims(1);\n    return tf.concat([yCoords, xCoords], 1);\n  });\n}\n", "import * as buildParts from './buildParts';\nimport * as decodePose from './decodePose';\nimport * as vectors from './vectors';\n\nconst kLocalMaximumRadius = 1;\nconst defaultOutputStride = 16;\n\nfunction withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId].position;\n    return vectors.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, squaredNmsRadius, instanceKeypoints) {\n  const notOverlappedKeypointScores = instanceKeypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinNmsRadiusOfCorrespondingPoint(existingPoses, squaredNmsRadius, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / instanceKeypoints.length;\n}\n\nexport function decodeMultiplePoses(scoresBuffer, offsetsBuffer, displacementsFwdBuffer, displacementsBwdBuffer, nmsRadius, maxDetections, scoreThreshold) {\n  const poses: Array<{ keypoints: any, score: number }> = [];\n  const queue = buildParts.buildPartWithScoreQueue(scoreThreshold, kLocalMaximumRadius, scoresBuffer);\n  const squaredNmsRadius = nmsRadius ^ 2;\n  // Generate at most maxDetections object instances per image in decreasing root part score order.\n  while (poses.length < maxDetections && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    const rootImageCoords = vectors.getImageCoords(root.part, defaultOutputStride, offsetsBuffer);\n    if (withinNmsRadiusOfCorrespondingPoint(poses, squaredNmsRadius, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    const keypoints = decodePose.decodePose(root, scoresBuffer, offsetsBuffer, defaultOutputStride, displacementsFwdBuffer, displacementsBwdBuffer);\n    const score = getInstanceScore(poses, squaredNmsRadius, keypoints);\n    if (score > scoreThreshold) poses.push({ keypoints, score });\n  }\n  return poses;\n}\n", "import * as kpt from './keypoints';\n\nexport function eitherPointDoesntMeetConfidence(a, b, minConfidence) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence) {\n  return kpt.connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nconst { NEGATIVE_INFINITY, POSITIVE_INFINITY } = Number;\nexport function getBoundingBox(keypoints) {\n  return keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: NEGATIVE_INFINITY,\n    maxY: NEGATIVE_INFINITY,\n    minX: POSITIVE_INFINITY,\n    minY: POSITIVE_INFINITY,\n  });\n}\n\nexport function getBoundingBoxPoints(keypoints) {\n  const { minX, minY, maxX, maxY } = getBoundingBox(keypoints);\n  return [{ x: minX, y: minY }, { x: maxX, y: minY }, { x: maxX, y: maxY }, { x: minX, y: maxY }];\n}\n\nexport async function toTensorBuffers3D(tensors) {\n  return Promise.all(tensors.map((tensor) => tensor.buffer()));\n}\n\nexport function scalePose(pose, scaleY, scaleX) {\n  return {\n    score: pose.score,\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score,\n      part,\n      position: { x: Math.trunc(position.x * scaleX), y: Math.trunc(position.y * scaleY) },\n    })),\n  };\n}\n\nexport function resizeTo(image, [targetH, targetW]) {\n  const input = image.squeeze(0);\n  const resized = input.resizeBilinear([targetH, targetW]);\n  input.dispose();\n  return resized;\n}\n\nexport function scaleAndFlipPoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]) {\n  const scaledPoses = poses.map((pose) => scalePose(pose, height / inputResolutionHeight, width / inputResolutionWidth));\n  return scaledPoses;\n}\n", "// https://storage.googleapis.com/tfjs-models/demos/handpose/index.html\n\nimport { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as handdetector from './handdetector';\nimport * as handpipeline from './handpipeline';\nimport * as anchors from './anchors';\n\nconst MESH_ANNOTATIONS = {\n  thumb: [1, 2, 3, 4],\n  indexFinger: [5, 6, 7, 8],\n  middleFinger: [9, 10, 11, 12],\n  ringFinger: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palmBase: [0],\n};\n\nexport class HandPose {\n  handPipeline: any;\n\n  constructor(handPipeline) {\n    this.handPipeline = handPipeline;\n  }\n\n  static getAnnotations() {\n    return MESH_ANNOTATIONS;\n  }\n\n  async estimateHands(input, config) {\n    const predictions = await this.handPipeline.estimateHands(input, config);\n    if (!predictions) return [];\n    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];\n    for (const prediction of predictions) {\n      const annotations = {};\n      if (prediction.landmarks) {\n        for (const key of Object.keys(MESH_ANNOTATIONS)) {\n          annotations[key] = MESH_ANNOTATIONS[key].map((index) => prediction.landmarks[index]);\n        }\n      }\n      const box = prediction.box ? [\n        Math.max(0, prediction.box.topLeft[0]),\n        Math.max(0, prediction.box.topLeft[1]),\n        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),\n        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),\n      ] : [];\n      const boxRaw = [\n        (prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.topLeft[1]) / input.shape[1],\n        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],\n        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],\n      ];\n      hands.push({ confidence: prediction.confidence, box, boxRaw, landmarks: prediction.landmarks, annotations });\n    }\n    return hands;\n  }\n}\n\nexport async function load(config) {\n  const [handDetectorModel, handPoseModel] = await Promise.all([\n    config.hand.enabled ? tf.loadGraphModel(config.hand.detector.modelPath, { fromTFHub: config.hand.detector.modelPath.includes('tfhub.dev') }) : null,\n    config.hand.landmarks ? tf.loadGraphModel(config.hand.skeleton.modelPath, { fromTFHub: config.hand.skeleton.modelPath.includes('tfhub.dev') }) : null,\n  ]);\n  const handDetector = new handdetector.HandDetector(handDetectorModel, handDetectorModel?.inputs[0].shape[2], anchors.anchors);\n  const handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel, handPoseModel?.inputs[0].shape[2]);\n  const handPose = new HandPose(handPipeline);\n  if (config.hand.enabled && config.debug) log(`load model: ${config.hand.detector.modelPath.match(/\\/(.*)\\./)[1]}`);\n  if (config.hand.landmarks && config.debug) log(`load model: ${config.hand.skeleton.modelPath.match(/\\/(.*)\\./)[1]}`);\n  return handPose;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\n\nexport class HandDetector {\n  model: any;\n  anchors: any;\n  anchorsTensor: any;\n  inputSize: number;\n  inputSizeTensor: any;\n  doubleInputSizeTensor: any;\n\n  constructor(model, inputSize, anchorsAnnotated) {\n    this.model = model;\n    this.anchors = anchorsAnnotated.map((anchor) => [anchor.x_center, anchor.y_center]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = inputSize;\n    this.inputSizeTensor = tf.tensor1d([inputSize, inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([inputSize * 2, inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    return tf.tidy(() => {\n      const boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n      const boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n      const boxCenterPoints = tf.add(tf.div(boxOffsets, this.inputSizeTensor), this.anchorsTensor);\n      const halfBoxSizes = tf.div(boxSizes, this.doubleInputSizeTensor);\n      const startPoints = tf.mul(tf.sub(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      const endPoints = tf.mul(tf.add(boxCenterPoints, halfBoxSizes), this.inputSizeTensor);\n      return tf.concat2d([startPoints, endPoints], 1);\n    });\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    return tf.tidy(() => {\n      const landmarks = tf.add(tf.div(rawPalmLandmarks.reshape([-1, 7, 2]), this.inputSizeTensor), this.anchors[index]);\n      return tf.mul(landmarks, this.inputSizeTensor);\n    });\n  }\n\n  async getBoxes(input, config) {\n    const batched = this.model.predict(input);\n    const predictions = batched.squeeze();\n    batched.dispose();\n    const scoresT = tf.tidy(() => tf.sigmoid(tf.slice(predictions, [0, 0], [-1, 1])).squeeze());\n    const scores = scoresT.dataSync();\n    const rawBoxes = tf.slice(predictions, [0, 1], [-1, 4]);\n    const boxes = this.normalizeBoxes(rawBoxes);\n    rawBoxes.dispose();\n    const filteredT = await tf.image.nonMaxSuppressionAsync(boxes, scores, config.hand.maxHands, config.hand.iouThreshold, config.hand.scoreThreshold);\n    const filtered = filteredT.arraySync();\n\n    scoresT.dispose();\n    filteredT.dispose();\n    const hands: Array<{ box: any, palmLandmarks: any, confidence: number }> = [];\n    for (const index of filtered) {\n      if (scores[index] >= config.hand.minConfidence) {\n        const matchingBox = tf.slice(boxes, [index, 0], [1, -1]);\n        const rawPalmLandmarks = tf.slice(predictions, [index, 5], [1, 14]);\n        const palmLandmarks = tf.tidy(() => this.normalizeLandmarks(rawPalmLandmarks, index).reshape([-1, 2]));\n        rawPalmLandmarks.dispose();\n        hands.push({ box: matchingBox, palmLandmarks, confidence: scores[index] });\n      }\n    }\n    predictions.dispose();\n    boxes.dispose();\n    return hands;\n  }\n\n  async estimateHandBounds(input, config) {\n    const inputHeight = input.shape[1];\n    const inputWidth = input.shape[2];\n    const image = tf.tidy(() => input.resizeBilinear([this.inputSize, this.inputSize]).div(127.5).sub(1));\n    const predictions = await this.getBoxes(image, config);\n    image.dispose();\n    const hands: Array<{}> = [];\n    if (!predictions || predictions.length === 0) return hands;\n    for (const prediction of predictions) {\n      const boxes = prediction.box.dataSync();\n      const startPoint = boxes.slice(0, 2);\n      const endPoint = boxes.slice(2, 4);\n      const palmLandmarks = prediction.palmLandmarks.arraySync();\n      prediction.box.dispose();\n      prediction.palmLandmarks.dispose();\n      hands.push(box.scaleBoxCoordinates({ startPoint, endPoint, palmLandmarks, confidence: prediction.confidence }, [inputWidth / this.inputSize, inputHeight / this.inputSize]));\n    }\n    return hands;\n  }\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]];\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize];\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]];\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]];\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as box from './box';\nimport * as util from './util';\n\n// const PALM_BOX_SHIFT_VECTOR = [0, -0.4];\nconst PALM_BOX_ENLARGE_FACTOR = 5; // default 3\n// const HAND_BOX_SHIFT_VECTOR = [0, -0.1]; // move detected hand box by x,y to ease landmark detection\nconst HAND_BOX_ENLARGE_FACTOR = 1.65; // default 1.65\nconst PALM_LANDMARK_IDS = [0, 5, 9, 13, 17, 1, 2];\nconst PALM_LANDMARKS_INDEX_OF_PALM_BASE = 0;\nconst PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE = 2;\n\nexport class HandPipeline {\n  handDetector: any;\n  landmarkDetector: any;\n  inputSize: number;\n  storedBoxes: any;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, landmarkDetector, inputSize) {\n    this.handDetector = handDetector;\n    this.landmarkDetector = landmarkDetector;\n    this.inputSize = inputSize;\n    this.storedBoxes = [];\n    this.skipped = 0;\n    this.detectedHands = 0;\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    // return box.enlargeBox(box.squarifyBox(box.shiftBox(boxAroundPalm, PALM_BOX_SHIFT_VECTOR)), PALM_BOX_ENLARGE_FACTOR);\n    return box.enlargeBox(box.squarifyBox(boxAroundPalm), PALM_BOX_ENLARGE_FACTOR);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    // const boxAroundHand = box.enlargeBox(box.squarifyBox(box.shiftBox(boundingBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n    const boxAroundHand = box.enlargeBox(box.squarifyBox(boundingBox), HAND_BOX_ENLARGE_FACTOR);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < PALM_LANDMARK_IDS.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[PALM_LANDMARK_IDS[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = box.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...box.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      coord[0] + originalBoxCenter[0],\n      coord[1] + originalBoxCenter[1],\n      coord[2],\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames unless we only want box to start with\n    let boxes;\n    if ((this.skipped === 0) || (this.skipped > config.hand.skipFrames) || !config.hand.landmarks || !config.videoOptimized) {\n      boxes = await this.handDetector.estimateHandBounds(image, config);\n      this.skipped = 0;\n    }\n    if (config.videoOptimized) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxHands) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{}> = [];\n\n    if (config.hand.skipInitial && this.detectedHands === 0) this.skipped = 0;\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_PALM_BASE], currentBox.palmLandmarks[PALM_LANDMARKS_INDEX_OF_MIDDLE_FINGER_BASE]) : 0;\n        const palmCenter = box.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = box.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = croppedInput.div(255);\n        croppedInput.dispose();\n        rotatedImage.dispose();\n        const [confidenceT, keypoints] = await this.landmarkDetector.predict(handImage);\n        handImage.dispose();\n        const confidence = confidenceT.dataSync()[0];\n        confidenceT.dispose();\n        if (confidence >= config.hand.minConfidence) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = keypointsReshaped.arraySync();\n          keypoints.dispose();\n          keypointsReshaped.dispose();\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = nextBoundingBox;\n          const result = {\n            landmarks: coords,\n            confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        keypoints.dispose();\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), HAND_BOX_ENLARGE_FACTOR);\n        const enlarged = box.enlargeBox(box.squarifyBox(currentBox), HAND_BOX_ENLARGE_FACTOR);\n        const result = {\n          confidence: currentBox.confidence,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    return hands;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n}\n", "export function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "export const anchors = [\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.015625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.046875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.078125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.109375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.140625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.171875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.203125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.234375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.265625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.296875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.328125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.359375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.390625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.421875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.453125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.484375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.515625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.546875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.578125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.609375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.640625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.671875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.703125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.734375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.765625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.796875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.828125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.859375,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.890625,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.921875,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.953125,\n    y_center: 0.015625,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 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y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.6875,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.8125,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n  {\n    w: 1,\n    h: 1,\n    x_center: 0.9375,\n    y_center: 0.9375,\n  },\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\nimport * as annotations from './annotations';\n\nlet model;\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.body.modelPath);\n    model.width = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[2].size);\n    model.height = parseInt(model.signature.inputs['input_1:0'].tensorShape.dim[1].size);\n    if (config.debug) log(`load model: ${config.body.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  if (!config.body.enabled) return null;\n  const imgSize = { width: image.shape[2], height: image.shape[1] };\n  const resize = tf.image.resizeBilinear(image, [model.width, model.height], false);\n  const normalize = tf.div(resize, [255.0]);\n  resize.dispose();\n  let points;\n  if (!config.profile) { // run through profiler or just execute\n    const resT = await model.predict(normalize);\n    // const segmentationT = resT.find((t) => (t.size === 16384))?.squeeze();\n    // const segmentation = segmentationT.arraySync(); // array 128 x 128\n    // segmentationT.dispose();\n    points = resT.find((t) => (t.size === 195 || t.size === 155)).dataSync(); // order of output tensors may change between models, full has 195 and upper has 155 items\n    resT.forEach((t) => t.dispose());\n  } else {\n    const profileData = await tf.profile(() => model.predict(normalize));\n    points = profileData.result.find((t) => (t.size === 195 || t.size === 155)).dataSync();\n    profileData.result.forEach((t) => t.dispose());\n    profile.run('blazepose', profileData);\n  }\n  normalize.dispose();\n  const keypoints: Array<{ id, part, position: { x, y, z }, score, presence }> = [];\n  const labels = points.length === 195 ? annotations.full : annotations.upper; // full model has 39 keypoints, upper has 31 keypoints\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    keypoints.push({\n      id: i,\n      part: labels[i],\n      position: {\n        x: Math.trunc(imgSize.width * points[depth * i + 0] / 255), // return normalized x value istead of 0..255\n        y: Math.trunc(imgSize.height * points[depth * i + 1] / 255), // return normalized y value istead of 0..255\n        z: Math.trunc(points[depth * i + 2]) + 0, // fix negative zero\n      },\n      score: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 3])))) / 100, // reverse sigmoid value\n      presence: (100 - Math.trunc(100 / (1 + Math.exp(points[depth * i + 4])))) / 100, // reverse sigmoid value\n    });\n  }\n  return [{ keypoints }];\n}\n", "export const full = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftPalm',\n  'rightPalm',\n  'leftIndex',\n  'rightIndex',\n  'leftPinky',\n  'rightPinky',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n  'leftHeel',\n  'rightHeel',\n  'leftFoot',\n  'rightFoot',\n  'midHip',\n  'forehead',\n  'leftThumb',\n  'leftHand',\n  'rightThumb',\n  'rightHand',\n];\n\nexport const upper = [\n  'nose',\n  'leftEyeInside',\n  'leftEye',\n  'leftEyeOutside',\n  'rightEyeInside',\n  'rightEye',\n  'rightEyeOutside',\n  'leftEar',\n  'rightEar',\n  'leftMouth',\n  'rightMouth',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'left:15',\n  'right:16',\n  'left:17',\n  'right:18',\n  'left:19',\n  'right:20',\n  'left:21',\n  'right:22',\n  'leftChest',\n  'rightChest',\n  'neck',\n  'forehead',\n  'left:27',\n  'right:28',\n  'left:29',\n  'right:30',\n];\n", "import { log } from '../log';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as profile from '../profile';\n\nlet model;\nlet last: Array<{}> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nconst scaleBox = 2.5; // increase box size\n// eslint-disable-next-line max-len\nconst labels = ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'vehicle', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'animal', 'bear', 'animal', 'animal', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'pastry', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'];\n\nexport async function load(config) {\n  if (!model) {\n    model = await tf.loadGraphModel(config.object.modelPath);\n    // @ts-ignore\n    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);\n    if (config.debug) log(`load model: ${config.object.modelPath.match(/\\/(.*)\\./)[1]}`);\n  }\n  return model;\n}\n\nasync function process(res, inputSize, outputShape, config) {\n  let results: Array<{ score: Number, strideSize: Number, class: Number, label: String, center: Number[], centerRaw: Number[], box: Number[], boxRaw: Number[] }> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      // log.info('Variation:', strideSize, 'strides', baseSize, 'baseSize');\n      const scores = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 80))?.squeeze();\n      const features = res.find((a) => (a.shape[1] === (baseSize ** 2) && a.shape[2] === 32))?.squeeze();\n      // log.state('Found features tensor:', features?.shape);\n      // log.state('Found scores tensor:', scores?.shape);\n      const scoreIdx = scores.argMax(1).dataSync(); // location of highest scores\n      const scoresMax = scores.max(1).dataSync(); // values of highest scores\n      const boxesMax = features.reshape([-1, 4, 8]); // reshape [32] to [4,8] where 8 is change of different features inside stride\n      const boxIdx = boxesMax.argMax(2).arraySync(); // what we need is indexes of features with highest scores, not values itself\n      for (let i = 0; i < scores.shape[0]; i++) {\n        if (scoreIdx[i] !== 0 && scoresMax[i] > config.object.minConfidence) {\n          const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n          const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n          const boxOffset = boxIdx[i].map((a) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n          let boxRaw = [ // results normalized to range 0..1\n            cx - (scaleBox / strideSize * boxOffset[0]),\n            cy - (scaleBox / strideSize * boxOffset[1]),\n            cx + (scaleBox / strideSize * boxOffset[2]),\n            cy + (scaleBox / strideSize * boxOffset[3]),\n          ];\n          boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords\n          const box = [ // results normalized to input image pixels\n            Math.max(0, (boxRaw[0] * outputShape[0])),\n            Math.max(0, (boxRaw[1] * outputShape[1])),\n            Math.min(1, (boxRaw[2] * outputShape[0]) - (boxRaw[0] * outputShape[0])),\n            Math.min(1, (boxRaw[3] * outputShape[1]) - (boxRaw[1] * outputShape[1])),\n          ];\n          const result = {\n            score: scoresMax[i],\n            strideSize,\n            class: scoreIdx[i] + 1,\n            label: labels[scoreIdx[i]],\n            center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n            centerRaw: [cx, cy],\n            box: box.map((a) => Math.trunc(a)),\n            boxRaw,\n          };\n          results.push(result);\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => a.boxRaw);\n  const nmsScores = results.map((a) => a.score);\n  const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxResults, config.object.iouThreshold, config.object.minConfidence);\n  const nmsIdx = nms.dataSync();\n  tf.dispose(nms);\n\n  // filter & sort results\n  results = results\n    .filter((a, idx) => nmsIdx.includes(idx))\n    // @ts-ignore\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image, config) {\n  if (!model) return null;\n  // console.log(skipped, config.object.skipFrames, config.videoOptimized, ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)));\n  if ((skipped < config.object.skipFrames) && config.videoOptimized && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  if (config.videoOptimized) skipped = 0;\n  else skipped = Number.MAX_SAFE_INTEGER;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2], image.shape[1]];\n    const resize = tf.image.resizeBilinear(image, [model.inputSize, model.inputSize], false);\n    const norm = resize.div(255);\n    resize.dispose();\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    norm.dispose();\n\n    let objectT;\n    if (!config.profile) {\n      if (config.object.enabled) objectT = await model.predict(transpose);\n    } else {\n      const profileObject = config.object.enabled ? await tf.profile(() => model.predict(transpose)) : {};\n      objectT = profileObject.result.clone();\n      profileObject.result.dispose();\n      profile.run('object', profileObject);\n    }\n    transpose.dispose();\n\n    const obj = await process(objectT, model.inputSize, outputSize, config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "export const body = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position.y < nose.position.y) && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position.y < nose.position.y)) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder) gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position.y > rightShoulder.position.y) ? 'left' : 'right'}` });\n  }\n  return gestures;\n};\n\nexport const face = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 0) {\n      const eyeFacing = res[i].mesh[33][2] - res[i].mesh[263][2];\n      if (Math.abs(eyeFacing) < 10) gestures.push({ face: i, gesture: 'facing camera' });\n      else gestures.push({ face: i, gesture: `facing ${eyeFacing < 0 ? 'right' : 'left'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2];\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.rightEyeIris) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) gestures.push({ iris: i, gesture: 'looking at camera' });\n  }\n  return gestures;\n};\n\nexport const hand = (res) => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: string }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: number }> = [];\n    for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n      // @ts-ignore\n      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward ${highest.name} up` });\n    }\n  }\n  return gestures;\n};\n", "// @ts-nocheck\n\nimport { log } from './log';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\n\nconst maxSize = 2048;\n// internal temp canvases\nlet inCanvas = null;\nlet outCanvas = null;\n// instance of fximage\nlet fx = null;\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {\n  let tensor;\n  if (input instanceof tf.Tensor) {\n    tensor = tf.clone(input);\n  } else {\n    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));\n    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = targetWidth * originalHeight / originalWidth;\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = targetHeight * originalWidth / originalHeight;\n    }\n    if (config.filter.width > 0) targetWidth = config.filter.width;\n    else if (config.filter.height > 0) targetWidth = originalWidth * (config.filter.height / originalHeight);\n    if (config.filter.height > 0) targetHeight = config.filter.height;\n    else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);\n    if (!targetWidth || !targetHeight) {\n      log('Human: invalid input', input);\n      return { tensor: null, canvas: null };\n    }\n    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {\n      inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;\n      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;\n    }\n    const ctx = inCanvas.getContext('2d');\n    if (input instanceof ImageData) ctx.putImageData(input, 0, 0);\n    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);\n    if (config.filter.enabled) {\n      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {\n        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');\n        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;\n        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;\n        // log('created FX filter');\n        fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')\n      }\n      if (!fx) return { tensor: null, canvas: inCanvas };\n      fx.reset();\n      fx.addFilter('brightness', config.filter.brightness); // must have at least one filter enabled\n      if (config.filter.contrast !== 0) fx.addFilter('contrast', config.filter.contrast);\n      if (config.filter.sharpness !== 0) fx.addFilter('sharpen', config.filter.sharpness);\n      if (config.filter.blur !== 0) fx.addFilter('blur', config.filter.blur);\n      if (config.filter.saturation !== 0) fx.addFilter('saturation', config.filter.saturation);\n      if (config.filter.hue !== 0) fx.addFilter('hue', config.filter.hue);\n      if (config.filter.negative) fx.addFilter('negative');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.vintage) fx.addFilter('brownie');\n      if (config.filter.sepia) fx.addFilter('sepia');\n      if (config.filter.kodachrome) fx.addFilter('kodachrome');\n      if (config.filter.technicolor) fx.addFilter('technicolor');\n      if (config.filter.polaroid) fx.addFilter('polaroid');\n      if (config.filter.pixelate !== 0) fx.addFilter('pixelate', config.filter.pixelate);\n      fx.apply(inCanvas);\n      // read pixel data\n      /*\n      const gl = outCanvas.getContext('webgl');\n      if (gl) {\n        const glBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 4);\n        const pixBuffer = new Uint8Array(outCanvas.width * outCanvas.height * 3);\n        gl.readPixels(0, 0, outCanvas.width, outCanvas.height, gl.RGBA, gl.UNSIGNED_BYTE, glBuffer);\n        // gl returns rbga while we only need rgb, so discarding alpha channel\n        // gl returns starting point as lower left, so need to invert vertical\n        let i = 0;\n        for (let y = outCanvas.height - 1; y >= 0; y--) {\n          for (let x = 0; x < outCanvas.width; x++) {\n            const index = (x + y * outCanvas.width) * 4;\n            pixBuffer[i++] = glBuffer[index + 0];\n            pixBuffer[i++] = glBuffer[index + 1];\n            pixBuffer[i++] = glBuffer[index + 2];\n          }\n        }\n        outCanvas.data = pixBuffer;\n      }\n      */\n    } else {\n      outCanvas = inCanvas;\n      if (fx) fx = null;\n    }\n    let pixels;\n    if (outCanvas.data) {\n      const shape = [outCanvas.height, outCanvas.width, 3];\n      pixels = tf.tensor3d(outCanvas.data, shape, 'int32');\n    } else if ((config.backend === 'webgl') || (outCanvas instanceof ImageData)) {\n      // tf kernel-optimized method to get imagedata, also if input is imagedata, just use it\n      pixels = tf.browser.fromPixels(outCanvas);\n    } else {\n      // cpu and wasm kernel does not implement efficient fromPixels method nor we can use canvas as-is, so we do a silly one more canvas\n      const tempCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');\n      tempCanvas.width = targetWidth;\n      tempCanvas.height = targetHeight;\n      const tempCtx = tempCanvas.getContext('2d');\n      tempCtx?.drawImage(outCanvas, 0, 0);\n      const data = tempCtx?.getImageData(0, 0, targetWidth, targetHeight);\n      pixels = tf.browser.fromPixels(data);\n    }\n    const casted = pixels.toFloat();\n    tensor = casted.expandDims(0);\n    pixels.dispose();\n    casted.dispose();\n  }\n  const canvas = config.filter.return ? outCanvas : null;\n  return { tensor, canvas };\n}\n", "/*\nWebGLImageFilter - MIT Licensed\n2013, Dominic Szablewski - phoboslab.org\n<https://github.com/phoboslab/WebGLImageFilter>\n*/\n\nfunction GLProgram(gl, vertexSource, fragmentSource) {\n  const _collect = function (source, prefix, collection) {\n    const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n    source.replace(r, (match, name) => {\n      collection[name] = 0;\n      return match;\n    });\n  };\n\n  const _compile = function (source, type) {\n    const shader = gl.createShader(type);\n    gl.shaderSource(shader, source);\n    gl.compileShader(shader);\n    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {\n      // @ts-ignore\n      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));\n    }\n    return shader;\n  };\n\n  this.uniform = {};\n  this.attribute = {};\n  const _vsh = _compile(vertexSource, gl.VERTEX_SHADER);\n  const _fsh = _compile(fragmentSource, gl.FRAGMENT_SHADER);\n  this.id = gl.createProgram();\n  gl.attachShader(this.id, _vsh);\n  gl.attachShader(this.id, _fsh);\n  gl.linkProgram(this.id);\n\n  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {\n    // @ts-ignore\n    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));\n  }\n\n  gl.useProgram(this.id);\n  // Collect attributes\n  _collect(vertexSource, 'attribute', this.attribute);\n  for (const a in this.attribute) this.attribute[a] = gl.getAttribLocation(this.id, a);\n  // Collect uniforms\n  _collect(vertexSource, 'uniform', this.uniform);\n  _collect(fragmentSource, 'uniform', this.uniform);\n  for (const u in this.uniform) this.uniform[u] = gl.getUniformLocation(this.id, u);\n}\n\n// export const GLImageFilter = function (params) {\nexport function GLImageFilter(params) {\n  if (!params) params = { };\n  let _drawCount = 0;\n  let _sourceTexture = null;\n  let _lastInChain = false;\n  let _currentFramebufferIndex = -1;\n  let _tempFramebuffers = [null, null];\n  let _filterChain = [];\n  let _width = -1;\n  let _height = -1;\n  let _vertexBuffer = null;\n  let _currentProgram = null;\n  const _filter = {};\n  const _canvas = params.canvas || document.createElement('canvas');\n  // key is the shader program source, value is the compiled program\n  const _shaderProgramCache = { };\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = _canvas.getContext('webgl');\n  if (!gl) throw new Error('Filter: getContext() failed');\n\n  this.addFilter = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const filter = _filter[name];\n    _filterChain.push({ func: filter, args });\n  };\n\n  this.reset = function () {\n    _filterChain = [];\n  };\n\n  const _resize = function (width, height) {\n    // Same width/height? Nothing to do here\n    if (width === _width && height === _height) { return; }\n    _canvas.width = width;\n    _width = width;\n    _canvas.height = height;\n    _height = height;\n    // Create the context if we don't have it yet\n    if (!_vertexBuffer) {\n      // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      const vertices = new Float32Array([\n        -1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0,\n        -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0,\n      ]);\n      // eslint-disable-next-line no-unused-expressions\n      (_vertexBuffer = gl.createBuffer(), gl.bindBuffer(gl.ARRAY_BUFFER, _vertexBuffer));\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, _width, _height);\n    // Delete old temp framebuffers\n    _tempFramebuffers = [null, null];\n  };\n\n  const _createFramebufferTexture = function (width, height) {\n    const fbo = gl.createFramebuffer();\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  };\n\n  const _getTempFramebuffer = function (index) {\n    // @ts-ignore\n    _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);\n    return _tempFramebuffers[index];\n  };\n\n  const _draw = function (flags = null) {\n    let source = null;\n    let target = null;\n    let flipY = false;\n    // Set up the source\n    if (_drawCount === 0) {\n      // First draw call - use the source texture\n      source = _sourceTexture;\n    } else {\n      // All following draw calls use the temp buffer last drawn to\n      // @ts-ignore\n      source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;\n    }\n    _drawCount++;\n    // Set up the target\n    if (_lastInChain && !(flags & DRAW.INTERMEDIATE)) {\n      // Last filter in our chain - draw directly to the WebGL Canvas. We may\n      // also have to flip the image vertically now\n      target = null;\n      flipY = _drawCount % 2 === 0;\n    } else {\n      // Intermediate draw call - get a temp buffer to draw to\n      _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;\n      // @ts-ignore\n      target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;\n    }\n    // Bind the source and target and draw the two triangles\n    gl.bindTexture(gl.TEXTURE_2D, source);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(_currentProgram.uniform.flipY, (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  };\n\n  this.apply = function (image) {\n    _resize(image.width, image.height);\n    _drawCount = 0;\n    // Create the texture for the input image if we haven't yet\n    if (!_sourceTexture) _sourceTexture = gl.createTexture();\n    gl.bindTexture(gl.TEXTURE_2D, _sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    // No filters? Just draw\n    if (_filterChain.length === 0) {\n      // const program = _compileShader(SHADER.FRAGMENT_IDENTITY);\n      _draw();\n      return _canvas;\n    }\n    for (let i = 0; i < _filterChain.length; i++) {\n      _lastInChain = (i === _filterChain.length - 1);\n      const f = _filterChain[i];\n      f.func.apply(this, f.args || []);\n    }\n    return _canvas;\n  };\n\n  const _compileShader = function (fragmentSource) {\n    if (_shaderProgramCache[fragmentSource]) {\n      _currentProgram = _shaderProgramCache[fragmentSource];\n      gl.useProgram(_currentProgram.id);\n      return _currentProgram;\n    }\n    // Compile shaders\n    const SHADER = {};\n    SHADER.VERTEX_IDENTITY = [\n      'precision highp float;',\n      'attribute vec2 pos;',\n      'attribute vec2 uv;',\n      'varying vec2 vUv;',\n      'uniform float flipY;',\n      'void main(void) {',\n      'vUv = uv;',\n      'gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);',\n      '}',\n    ].join('\\n');\n    SHADER.FRAGMENT_IDENTITY = [\n      'precision highp float;',\n      'varying vec2 vUv;',\n      'uniform sampler2D texture;',\n      'void main(void) {',\n      'gl_FragColor = texture2D(texture, vUv);',\n      '}',\n    ].join('\\n');\n    _currentProgram = new GLProgram(gl, SHADER.VERTEX_IDENTITY, fragmentSource);\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(_currentProgram.attribute.pos);\n    gl.vertexAttribPointer(_currentProgram.attribute.pos, 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(_currentProgram.attribute.uv);\n    gl.vertexAttribPointer(_currentProgram.attribute.uv, 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    _shaderProgramCache[fragmentSource] = _currentProgram;\n    return _currentProgram;\n  };\n\n  // -------------------------------------------------------------------------\n  // Color Matrix Filter\n  _filter.colorMatrix = function (matrix) {\n    // Create a Float32 Array and normalize the offset component to 0-1\n    const m = new Float32Array(matrix);\n    m[4] /= 255;\n    m[9] /= 255;\n    m[14] /= 255;\n    m[19] /= 255;\n    // Can we ignore the alpha value? Makes things a bit faster.\n    const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0)\n      ? _filter.colorMatrix.SHADER.WITHOUT_ALPHA\n      : _filter.colorMatrix.SHADER.WITH_ALPHA;\n    const program = _compileShader(shader);\n    gl.uniform1fv(program.uniform.m, m);\n    _draw();\n  };\n  _filter.colorMatrix.SHADER = {};\n  _filter.colorMatrix.SHADER.WITH_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];',\n    'gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];',\n    '}',\n  ].join('\\n');\n  _filter.colorMatrix.SHADER.WITHOUT_ALPHA = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform float m[20];',\n    'void main(void) {',\n    'vec4 c = texture2D(texture, vUv);',\n    'gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];',\n    'gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];',\n    'gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];',\n    'gl_FragColor.a = c.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.brightness = function (brightness) {\n    const b = (brightness || 0) + 1;\n    _filter.colorMatrix([\n      b, 0, 0, 0, 0,\n      0, b, 0, 0, 0,\n      0, 0, b, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.saturation = function (amount) {\n    const x = (amount || 0) * 2 / 3 + 1;\n    const y = ((x - 1) * -0.5);\n    _filter.colorMatrix([\n      x, y, y, 0, 0,\n      y, x, y, 0, 0,\n      y, y, x, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturate = function () {\n    _filter.saturation(-1);\n  };\n\n  _filter.contrast = function (amount) {\n    const v = (amount || 0) + 1;\n    const o = -128 * (v - 1);\n\n    _filter.colorMatrix([\n      v, 0, 0, 0, o,\n      0, v, 0, 0, o,\n      0, 0, v, 0, o,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.negative = function () {\n    _filter.contrast(-2);\n  };\n\n  _filter.hue = function (rotation) {\n    rotation = (rotation || 0) / 180 * Math.PI;\n    const cos = Math.cos(rotation);\n    const sin = Math.sin(rotation);\n    const lumR = 0.213;\n    const lumG = 0.715;\n    const lumB = 0.072;\n\n    _filter.colorMatrix([\n      lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n      lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n      lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.desaturateLuminance = function () {\n    _filter.colorMatrix([\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.sepia = function () {\n    _filter.colorMatrix([\n      0.393, 0.7689999, 0.18899999, 0, 0,\n      0.349, 0.6859999, 0.16799999, 0, 0,\n      0.272, 0.5339999, 0.13099999, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.brownie = function () {\n    _filter.colorMatrix([\n      0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n      -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n      0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.vintagePinhole = function () {\n    _filter.colorMatrix([\n      0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n      0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n      0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.kodachrome = function () {\n    _filter.colorMatrix([\n      1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n      -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n      -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.technicolor = function () {\n    _filter.colorMatrix([\n      1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n      -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n      -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.polaroid = function () {\n    _filter.colorMatrix([\n      1.438, -0.062, -0.062, 0, 0,\n      -0.122, 1.378, -0.122, 0, 0,\n      -0.016, -0.016, 1.483, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  _filter.shiftToBGR = function () {\n    _filter.colorMatrix([\n      0, 0, 1, 0, 0,\n      0, 1, 0, 0, 0,\n      1, 0, 0, 0, 0,\n      0, 0, 0, 1, 0,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Convolution Filter\n  _filter.convolution = function (matrix) {\n    const m = new Float32Array(matrix);\n    const pixelSizeX = 1 / _width;\n    const pixelSizeY = 1 / _height;\n    const program = _compileShader(_filter.convolution.SHADER);\n    gl.uniform1fv(program.uniform.m, m);\n    gl.uniform2f(program.uniform.px, pixelSizeX, pixelSizeY);\n    _draw();\n  };\n\n  _filter.convolution.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'uniform float m[9];',\n    'void main(void) {',\n    'vec4 c11 = texture2D(texture, vUv - px);', // top left\n    'vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));', // top center\n    'vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));', // top right\n    'vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );', // mid left\n    'vec4 c22 = texture2D(texture, vUv);', // mid center\n    'vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );', // mid right\n    'vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );', // bottom left\n    'vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );', // bottom center\n    'vec4 c33 = texture2D(texture, vUv + px );', // bottom right\n    'gl_FragColor = ',\n    'c11 * m[0] + c12 * m[1] + c22 * m[2] +',\n    'c21 * m[3] + c22 * m[4] + c23 * m[5] +',\n    'c31 * m[6] + c32 * m[7] + c33 * m[8];',\n    'gl_FragColor.a = c22.a;',\n    '}',\n  ].join('\\n');\n\n  _filter.detectEdges = function () {\n    _filter.convolution.call(this, [\n      0, 1, 0,\n      1, -4, 1,\n      0, 1, 0,\n    ]);\n  };\n\n  _filter.sobelX = function () {\n    _filter.convolution.call(this, [\n      -1, 0, 1,\n      -2, 0, 2,\n      -1, 0, 1,\n    ]);\n  };\n\n  _filter.sobelY = function () {\n    _filter.convolution.call(this, [\n      -1, -2, -1,\n      0, 0, 0,\n      1, 2, 1,\n    ]);\n  };\n\n  _filter.sharpen = function (amount) {\n    const a = amount || 1;\n    _filter.convolution.call(this, [\n      0, -1 * a, 0,\n      -1 * a, 1 + 4 * a, -1 * a,\n      0, -1 * a, 0,\n    ]);\n  };\n\n  _filter.emboss = function (size) {\n    const s = size || 1;\n    _filter.convolution.call(this, [\n      -2 * s, -1 * s, 0,\n      -1 * s, 1, 1 * s,\n      0, 1 * s, 2 * s,\n    ]);\n  };\n\n  // -------------------------------------------------------------------------\n  // Blur Filter\n  _filter.blur = function (size) {\n    const blurSizeX = (size / 7) / _width;\n    const blurSizeY = (size / 7) / _height;\n    const program = _compileShader(_filter.blur.SHADER);\n    // Vertical\n    gl.uniform2f(program.uniform.px, 0, blurSizeY);\n    _draw(DRAW.INTERMEDIATE);\n    // Horizontal\n    gl.uniform2f(program.uniform.px, blurSizeX, 0);\n    _draw();\n  };\n\n  _filter.blur.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform sampler2D texture;',\n    'uniform vec2 px;',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;',\n    'gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;',\n    '}',\n  ].join('\\n');\n\n  // -------------------------------------------------------------------------\n  // Pixelate Filter\n  _filter.pixelate = function (size) {\n    const blurSizeX = (size) / _width;\n    const blurSizeY = (size) / _height;\n    const program = _compileShader(_filter.pixelate.SHADER);\n    // Horizontal\n    gl.uniform2f(program.uniform.size, blurSizeX, blurSizeY);\n    _draw();\n  };\n\n  _filter.pixelate.SHADER = [\n    'precision highp float;',\n    'varying vec2 vUv;',\n    'uniform vec2 size;',\n    'uniform sampler2D texture;',\n    'vec2 pixelate(vec2 coord, vec2 size) {',\n    'return floor( coord / size ) * size;',\n    '}',\n    'void main(void) {',\n    'gl_FragColor = vec4(0.0);',\n    'vec2 coord = pixelate(vUv, size);',\n    'gl_FragColor += texture2D(texture, coord);',\n    '}',\n  ].join('\\n');\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\nexport default {\n  backend: 'webgl',          // select tfjs backend to use\n                             // can be 'webgl', 'wasm', 'cpu', or 'humangl' which is a custom version of webgl\n                             // leave as empty string to continue using default backend\n                             // when backend is set outside of Human library\n  wasmPath: '../assets/',    // path for wasm binaries\n                             // only used for backend: wasm\n  debug: true,               // print additional status messages to console\n  async: true,               // execute enabled models in parallel\n                             // this disables per-model performance data but\n                             // slightly increases performance\n                             // cannot be used if profiling is enabled\n  profile: false,            // enable tfjs profiling\n                             // this has significant performance impact\n                             // only enable for debugging purposes\n                             // currently only implemented for age,gender,emotion models\n  deallocate: false,         // aggresively deallocate gpu memory after each usage\n                             // only valid for webgl backend and only during first call\n                             // cannot be changed unless library is reloaded\n                             // this has significant performance impact\n                             // only enable on low-memory devices\n  scoped: false,             // enable scoped runs\n                             // some models *may* have memory leaks,\n                             // this wrapps everything in a local scope at a cost of performance\n                             // typically not needed\n  videoOptimized: true,      // perform additional optimizations when input is video,\n                             // must be disabled for images\n                             // basically this skips object box boundary detection for every n frames\n                             // while maintaining in-box detection since objects cannot move that fast\n  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'\n                             // warmup pre-initializes all models for faster inference but can take\n                             // significant time on startup\n  filter: {\n    enabled: true,           // enable image pre-processing filters\n    width: 0,                // resize input width\n    height: 0,               // resize input height\n                             // if both width and height are set to 0, there is no resizing\n                             // if just one is set, second one is scaled automatically\n                             // if both are set, values are used as-is\n    return: true,            // return processed canvas imagedata in result\n    brightness: 0,           // range: -1 (darken) to 1 (lighten)\n    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)\n    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)\n    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)\n    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)\n    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)\n    negative: false,         // image negative\n    sepia: false,            // image sepia colors\n    vintage: false,          // image vintage colors\n    kodachrome: false,       // image kodachrome colors\n    technicolor: false,      // image technicolor colors\n    polaroid: false,         // image polaroid camera effect\n    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)\n  },\n\n  gesture: {\n    enabled: true,           // enable simple gesture recognition\n  },\n\n  face: {\n    enabled: true,           // controls if specified modul is enabled\n                             // face.enabled is required for all face models:\n                             // detector, mesh, iris, age, gender, emotion\n                             // (note: module is not loaded until it is required)\n    detector: {\n      modelPath: '../models/blazeface-back.json',\n      rotation: false,       // use best-guess rotated face image or just box with rotation as-is\n                             // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees\n                             // this parameter is not valid in nodejs\n      maxFaces: 10,          // maximum number of faces detected in the input\n                             // should be set to the minimum number for performance\n      skipFrames: 21,        // how many frames to go without re-running the face bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated face analysis as the head probably hasn't moved much\n                             // in short time (10 * 1/25 = 0.25 sec)\n      skipInitial: false,    // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n      minConfidence: 0.2,    // threshold for discarding a prediction\n      iouThreshold: 0.1,     // threshold for deciding whether boxes overlap too much in\n                             // non-maximum suppression (0.1 means drop if overlap 10%)\n      scoreThreshold: 0.2,   // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression,\n                             // this is applied on detection objects only and before minConfidence\n      return: false,         // return extracted face as tensor\n    },\n\n    mesh: {\n      enabled: true,\n      modelPath: '../models/facemesh.json',\n    },\n\n    iris: {\n      enabled: true,\n      modelPath: '../models/iris.json',\n    },\n\n    age: {\n      enabled: true,\n      modelPath: '../models/age.json',\n      skipFrames: 31,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    gender: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      modelPath: '../models/gender.json',\n      skipFrames: 32,        // how many frames to go without re-running the detector\n                             // only used for video inputs\n    },\n\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,    // threshold for discarding a prediction\n      skipFrames: 33,        // how many frames to go without re-running the detector\n      modelPath: '../models/emotion.json',\n    },\n\n    embedding: {\n      enabled: false,        // to improve accuracy of face embedding extraction it is\n                             // highly recommended to enable detector.rotation and mesh.enabled\n      modelPath: '../models/mobileface.json',\n    },\n  },\n\n  body: {\n    enabled: true,\n    modelPath: '../models/posenet.json', // can be 'posenet' or 'blazepose'\n    maxDetections: 10,       // maximum number of people detected in the input\n                             // should be set to the minimum number for performance\n                             // only valid for posenet as blazepose only detects single pose\n    scoreThreshold: 0.3,     // threshold for deciding when to remove boxes based on score\n                             // in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression\n                             // only valid for posenet as blazepose only detects single pose\n  },\n\n  hand: {\n    enabled: true,\n    rotation: false,         // use best-guess rotated hand image or just box with rotation as-is\n                             // false means higher performance, but incorrect finger mapping if hand is inverted\n    skipFrames: 12,          // how many frames to go without re-running the hand bounding box detector\n                             // only used for video inputs\n                             // e.g., if model is running st 25 FPS, we can re-use existing bounding\n                             // box for updated hand skeleton analysis as the hand probably\n                             // hasn't moved much in short time (10 * 1/25 = 0.25 sec)\n    skipInitial: false,      // if previous detection resulted in no faces detected,\n                             // should skipFrames be reset immediately\n    minConfidence: 0.1,      // threshold for discarding a prediction\n    iouThreshold: 0.1,       // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    scoreThreshold: 0.5,     // threshold for deciding when to remove boxes based on\n                             // score in non-maximum suppression\n    maxHands: 1,             // maximum number of hands detected in the input\n                             // should be set to the minimum number for performance\n    landmarks: true,         // detect hand landmarks or just hand boundary box\n    detector: {\n      modelPath: '../models/handdetect.json',\n    },\n    skeleton: {\n      modelPath: '../models/handskeleton.json',\n    },\n  },\n\n  object: {\n    enabled: false,\n    modelPath: '../models/nanodet.json',\n    minConfidence: 0.15,     // threshold for discarding a prediction\n    iouThreshold: 0.25,      // threshold for deciding whether boxes overlap too much\n                             // in non-maximum suppression\n    maxResults: 10,          // maximum number of objects detected in the input\n    skipFrames: 13,          // how many frames to go without re-running the detector\n  },\n};\n", "// data:image/jpeg;base64,\nexport const face = `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\nWmlQ6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"import config from '../config';\nimport { TRI468 as triangulation } from './blazeface/coords';\n\nexport const drawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>20,\n  lineWidth: <number>6,\n  pointSize: <number>2,\n  roundRect: <number>28,\n  drawPoints: <Boolean>false,\n  drawLabels: <Boolean>true,\n  drawBoxes: <Boolean>true,\n  drawPolygons: <Boolean>true,\n  fillPolygons: <Boolean>false,\n  useDepth: <Boolean>true,\n  useCurves: <Boolean>false,\n  bufferedOutput: <Boolean>false,\n  useRawBoxes: <Boolean>false,\n};\n\nfunction point(ctx, x, y, z = null) {\n  ctx.fillStyle = drawOptions.useDepth && z ? `rgba(${127.5 + (2 * (z || 0))}, ${127.5 - (2 * (z || 0))}, 255, 0.3)` : drawOptions.color;\n  ctx.beginPath();\n  ctx.arc(x, y, drawOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nfunction rect(ctx, x, y, width, height) {\n  ctx.beginPath();\n  if (drawOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.lineWidth = drawOptions.lineWidth;\n    ctx.moveTo(x + drawOptions.roundRect, y);\n    ctx.lineTo(x + width - drawOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + drawOptions.roundRect);\n    ctx.lineTo(x + width, y + height - drawOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - drawOptions.roundRect, y + height);\n    ctx.lineTo(x + drawOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - drawOptions.roundRect);\n    ctx.lineTo(x, y + drawOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + drawOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nfunction lines(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.fillStyle = drawOptions.useDepth && pt[2] ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.3)` : drawOptions.color;\n    ctx.lineTo(pt[0], parseInt(pt[1]));\n  }\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nfunction curves(ctx, points: number[] = []) {\n  if (points === undefined || points.length === 0) return;\n  if (!drawOptions.useCurves || points.length <= 2) {\n    lines(ctx, points);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (drawOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport async function gesture(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.font = drawOptions.font;\n  ctx.fillStyle = drawOptions.color;\n  let i = 1;\n  for (let j = 0; j < result.length; j++) {\n    let where:any[] = [];\n    let what:any[] = [];\n    [where, what] = Object.entries(result[j]);\n    if ((what.length > 1) && (what[1].length > 0)) {\n      const person = where[1] > 0 ? `#${where[1]}` : '';\n      const label = `${where[0]} ${person}: ${what[1]}`;\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(label, 8, 2 + (i * drawOptions.lineHeight));\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(label, 6, 0 + (i * drawOptions.lineHeight));\n      i += 1;\n    }\n  }\n}\n\nexport async function face(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  for (const f of result) {\n    ctx.font = drawOptions.font;\n    ctx.strokeStyle = drawOptions.color;\n    ctx.fillStyle = drawOptions.color;\n    if (drawOptions.drawBoxes) {\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);\n      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);\n    }\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);\n    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);\n    // if (f.genderConfidence) labels.push(f.gender);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`iris distance: ${f.iris}`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      labels.push(emotion.join(' '));\n    }\n    if (f.angle && f.angle.roll) labels.push(`roll: ${Math.trunc(100 * f.angle.roll) / 100} yaw:${Math.trunc(100 * f.angle.yaw) / 100} pitch:${Math.trunc(100 * f.angle.pitch) / 100}`);\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = drawOptions.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * drawOptions.lineHeight + f.box[1];\n      if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n        ctx.fillStyle = drawOptions.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = drawOptions.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n    ctx.lineWidth = 1;\n    if (f.mesh && f.mesh.length > 0) {\n      if (drawOptions.drawPoints) {\n        for (const pt of f.mesh) point(ctx, pt[0], pt[1], pt[2]);\n        // for (const pt of f.meshRaw) point(ctx, pt[0] * inCanvas.offsetWidth, pt[1] * inCanvas.offsetHeight, pt[2]);\n      }\n      if (drawOptions.drawPolygons) {\n        ctx.lineWidth = 1;\n        for (let i = 0; i < triangulation.length / 3; i++) {\n          const points = [\n            triangulation[i * 3 + 0],\n            triangulation[i * 3 + 1],\n            triangulation[i * 3 + 2],\n          ].map((index) => f.mesh[index]);\n          lines(ctx, points);\n        }\n        // iris: array[center, left, top, right, bottom]\n        if (f.annotations && f.annotations.leftEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.leftEyeIris[4][1] - f.annotations.leftEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.leftEyeIris[0][0], f.annotations.leftEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n        if (f.annotations && f.annotations.rightEyeIris) {\n          ctx.strokeStyle = drawOptions.useDepth ? 'rgba(255, 200, 255, 0.3)' : drawOptions.color;\n          ctx.beginPath();\n          const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;\n          const sizeY = Math.abs(f.annotations.rightEyeIris[4][1] - f.annotations.rightEyeIris[2][1]) / 2;\n          ctx.ellipse(f.annotations.rightEyeIris[0][0], f.annotations.rightEyeIris[0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n          ctx.stroke();\n          if (drawOptions.fillPolygons) {\n            ctx.fillStyle = drawOptions.useDepth ? 'rgba(255, 255, 200, 0.3)' : drawOptions.color;\n            ctx.fill();\n          }\n        }\n      }\n    }\n  }\n}\n\nconst lastDrawnPose:any[] = [];\nexport async function body(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    // result[i].keypoints = result[i].keypoints.filter((a) => a.score > 0.5);\n    if (!lastDrawnPose[i] && drawOptions.bufferedOutput) lastDrawnPose[i] = { ...result[i] };\n    ctx.strokeStyle = drawOptions.color;\n    ctx.lineWidth = drawOptions.lineWidth;\n    if (drawOptions.drawPoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        ctx.fillStyle = drawOptions.useDepth && result[i].keypoints[pt].position.z ? `rgba(${127.5 + (2 * result[i].keypoints[pt].position.z)}, ${127.5 - (2 * result[i].keypoints[pt].position.z)}, 255, 0.5)` : drawOptions.color;\n        if (drawOptions.bufferedOutput) {\n          lastDrawnPose[i].keypoints[pt][0] = (lastDrawnPose[i].keypoints[pt][0] + result[i].keypoints[pt].position.x) / 2;\n          lastDrawnPose[i].keypoints[pt][1] = (lastDrawnPose[i].keypoints[pt][1] + result[i].keypoints[pt].position.y) / 2;\n          point(ctx, lastDrawnPose[i].keypoints[pt][0], lastDrawnPose[i].keypoints[pt][1]);\n        } else {\n          point(ctx, result[i].keypoints[pt].position.x, result[i].keypoints[pt].position.y);\n        }\n      }\n    }\n    if (drawOptions.drawLabels) {\n      ctx.font = drawOptions.font;\n      for (const pt of result[i].keypoints) {\n        ctx.fillStyle = drawOptions.useDepth && pt.position.z ? `rgba(${127.5 + (2 * pt.position.z)}, ${127.5 - (2 * pt.position.z)}, 255, 0.5)` : drawOptions.color;\n        ctx.fillText(`${pt.part}`, pt.position.x + 4, pt.position.y + 4);\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      let part;\n      const points: any[] = [];\n      // torso\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      if (points.length === 5) lines(ctx, points); // only draw if we have complete torso\n      // leg left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // leg right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightHip');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightKnee');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightAnkle');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightHeel');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightFoot');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm left\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'leftShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'leftPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // arm right\n      points.length = 0;\n      part = result[i].keypoints.find((a) => a.part === 'rightShoulder');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightElbow');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightWrist');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      part = result[i].keypoints.find((a) => a.part === 'rightPalm');\n      if (part && part.score > config.body.scoreThreshold) points.push([part.position.x, part.position.y]);\n      curves(ctx, points);\n      // draw all\n    }\n  }\n}\n\nexport async function hand(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText('hand', h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText('hand', h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n    if (drawOptions.drawPoints) {\n      if (h.landmarks && h.landmarks.length > 0) {\n        for (const pt of h.landmarks) {\n          ctx.fillStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * pt[2])}, ${127.5 - (2 * pt[2])}, 255, 0.5)` : drawOptions.color;\n          point(ctx, pt[0], pt[1]);\n        }\n      }\n    }\n    if (drawOptions.drawPolygons) {\n      const addPart = (part) => {\n        if (!part) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.lineWidth = drawOptions.lineWidth;\n          ctx.beginPath();\n          ctx.strokeStyle = drawOptions.useDepth ? `rgba(${127.5 + (2 * part[i][2])}, ${127.5 - (2 * part[i][2])}, 255, 0.5)` : drawOptions.color;\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      addPart(h.annotations.indexFinger);\n      addPart(h.annotations.middleFinger);\n      addPart(h.annotations.ringFinger);\n      addPart(h.annotations.pinky);\n      addPart(h.annotations.thumb);\n      // addPart(hand.annotations.palmBase);\n    }\n  }\n}\n\nexport async function object(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  const ctx = inCanvas.getContext('2d');\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = drawOptions.font;\n  for (const h of result) {\n    if (drawOptions.drawBoxes) {\n      ctx.strokeStyle = drawOptions.color;\n      ctx.fillStyle = drawOptions.color;\n      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);\n      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);\n      if (drawOptions.drawLabels) {\n        const label = `${Math.round(100 * h.score)}% ${h.label}`;\n        if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {\n          ctx.fillStyle = drawOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = drawOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + drawOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\nexport async function canvas(inCanvas, outCanvas) {\n  if (!inCanvas || !outCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement) || !(outCanvas instanceof HTMLCanvasElement)) return;\n  const outCtx = inCanvas.getContext('2d');\n  outCtx?.drawImage(inCanvas, 0, 0);\n}\n\nexport async function all(inCanvas, result) {\n  if (!result || !inCanvas) return;\n  if (!(inCanvas instanceof HTMLCanvasElement)) return;\n  face(inCanvas, result.face);\n  body(inCanvas, result.body);\n  hand(inCanvas, result.hand);\n  gesture(inCanvas, result.gesture);\n  object(inCanvas, result.object);\n}\n"],
+  "mappings": 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diff --git a/dist/tfjs.esm.js b/dist/tfjs.esm.js
index 76c1a082..de4cabf4 100644
--- a/dist/tfjs.esm.js
+++ b/dist/tfjs.esm.js
@@ -5,31 +5,31 @@
   author: <https://github.com/vladmandic>'
   */
 
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n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*zh(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 rl||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*zh(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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n=v(r,"x","batchToSpaceND"),o=e.reduce((i,l)=>i*l);E(n.rank>=1+e.length,()=>`input rank is ${n.rank} but should be > than blockShape.length ${e.length}`),E(t.length===e.length,()=>`crops.length is ${t.length} but should be equal to blockShape.length  ${e.length}`),E(n.shape[0]%o==0,()=>`input tensor batch is ${n.shape[0]} but is not divisible by the product of the elements of blockShape ${e.join(" * ")} === ${o}`);let s={x:n},a={blockShape:e,crops:t};return D.runKernel(ra,s,a)}var ka=T({batchToSpaceND_:sW});function zN(r){let e;return r.rank===0||r.rank===1?e=L(r,[1,1,1,r.size]):r.rank===2?e=L(r,[1,1,r.shape[0],r.shape[1]]):r.rank===3?e=L(r,[1,r.shape[0],r.shape[1],r.shape[2]]):e=r,e}function iW(r,e,t,n,o,s){s==null&&(s=.001);let a=v(r,"x","batchNorm"),i=v(e,"mean","batchNorm"),l=v(t,"variance","batchNorm"),u;o!=null&&(u=v(o,"scale","batchNorm"));let c;n!=null&&(c=v(n,"offset","batchNorm")),E(i.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal 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${u.rank}.`),c!=null&&E(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),Lo(a,i,l,c,u,s)}var ww=T({batchNorm2d_:aW});function lW(r,e,t,n,o,s){let a=v(r,"x","batchNorm"),i=v(e,"mean","batchNorm"),l=v(t,"variance","batchNorm"),u;o!=null&&(u=v(o,"scale","batchNorm"));let c;return n!=null&&(c=v(n,"offset","batchNorm")),E(a.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${a.rank}.`),E(i.rank===3||i.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${i.rank}.`),E(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&E(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),c!=null&&E(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),Lo(a,i,l,c,u,s)}var kw=T({batchNorm3d_:lW});function uW(r,e,t,n,o,s){let a=v(r,"x","batchNorm"),i=v(e,"mean","batchNorm"),l=v(t,"variance","batchNorm"),u;o!=null&&(u=v(o,"scale","batchNorm"));let c;return n!=null&&(c=v(n,"offset","batchNorm")),E(a.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${a.rank}.`),E(i.rank===4||i.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`),E(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&E(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&E(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),Lo(a,i,l,c,u,s)}var _w=T({batchNorm4d_:uW});function cW(r,e,t){let n=v(r,"x","bincount"),o=v(e,"weights","bincount");E(n.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${n.dtype}`),E(t>=0,()=>`size must be non-negative, but got ${t}.`),E(o.size===n.size||o.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${n.shape}, weights shape: ${o.shape}.`);let s={x:n,weights:o},a={size:t};return D.runKernel(Vl,s,a)}var vw=T({bincount_:cW});function pW(r,e){let t=v(r,"broadcastTo","x"),n=t.shape;if(e.some(u=>!(u>0)||u%1!=0))throw new Error(`broadcastTo(): Invalid broadcast shape [${e}].`);if(e.length<t.rank)throw new Error(`broadcastTo(): shape.length=${e.length} < input.rank=${t.rank}.`);if(e.length>t.rank){let u=t.shape.slice();for(;u.length<e.length;)u.unshift(1);t=L(t,u)}let o=t.shape,s=Array.from(e);for(let u=e.length-1;u>=0;u--)if(o[u]===e[u])s[u]=1;else if(t.shape[u]!==1)throw new Error(`broadcastTo(): [${n}] cannot be broadcast to [${e}].`);if(s.map((u,c)=>u>1?c:-1).filter(u=>u>=0).length===0)return Pn(t);let i={x:t},l={reps:s};return D.runKernel(kn,i,l)}var al=T({broadcastTo_:pW});function mW(r){let t={x:v(r,"x","ceil")};return D.runKernel(Yn,t)}var Dm=T({ceil_:mW});function fW(r,e,t){let n=v(r,"x","clipByValue");E(e<=t,()=>`Error in clip: min (${e}) must be less than or equal to max (${t}).`);let o={x:n},s={clipValueMin:e,clipValueMax:t};return D.runKernel(Rn,o,s)}var ir=T({clipByValue_:fW});function dW(r){return Ze(r,0)}var Cw=T({concat1d_:dW});function hW(r,e){return Ze(r,e)}var Iw=T({concat2d_:hW});function gW(r,e){return Ze(r,e)}var Nw=T({concat3d_:gW});function xW(r,e){return Ze(r,e)}var Sw=T({concat4d_:xW});function yW(r,e,t,n,o="NHWC",s=[1,1],a){let i=v(r,"x","conv2d"),l=v(e,"filter","conv2d"),u=i,c=!1;i.rank===3&&(c=!0,u=L(i,[1,i.shape[0],i.shape[1],i.shape[2]])),E(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),E(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),a!=null&&E(nt(n),()=>`Error in conv2d: pad must be an integer when using, dimRoundingMode ${a} but got pad ${n}.`);let p=o==="NHWC"?u.shape[3]:u.shape[1];E(p===l.shape[2],()=>`Error in conv2d: depth of input (${p}) must match input depth for filter ${l.shape[2]}.`),E(kr(t,s),()=>`Error in conv2D: Either strides or dilations must be 1. 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Got stride ${t} and dilation '${s}'`),E(o==="NWC",()=>`Error in conv1d: got dataFormat of ${o} but only NWC is currently supported.`);let p=L(l,[1,l.shape[0],l.shape[1],l.shape[2]]),m=L(u,[u.shape[0],1,u.shape[1],u.shape[2]]),g=Kr(m,p,[1,t],n,"NHWC",[1,s],a);return c?L(g,[g.shape[2],g.shape[3]]):L(g,[g.shape[0],g.shape[2],g.shape[3]])}var _u=T({conv1d_:bW});function wW(r,e,t,n,o,s="NHWC",a){E(r.length===e.rank,()=>`Length of inShape (${r.length}) and rank of dy (${e.rank}) must match`);let i=r,l=e,u=!1;e.rank===3&&(u=!0,l=L(e,[1,e.shape[0],e.shape[1],e.shape[2]]),i=[1,r[0],r[1],r[2]]),E(i.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${i.length}.`),E(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),E(t.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${t.rank}`);let c=s==="NHWC"?i[3]:i[1],p=s==="NHWC"?l.shape[3]:l.shape[1];E(c===t.shape[2],()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${t.shape[2]}.`),E(p===t.shape[3],()=>`Error in conv2dDerInput: depth of output (${p}) must match output depth for filter ${t.shape[3]}.`),a!=null&&E(nt(o),()=>`Error in conv2dDerInput: pad must be an integer when using, dimRoundingMode ${a} but got pad ${o}.`);let m={dy:l,filter:t},f={strides:n,pad:o,dataFormat:s,dimRoundingMode:a,inputShape:i},d=D.runKernel(Jn,m,f);return u?L(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var Xc=T({conv2DBackpropInput_:wW});function kW(r,e,t,n,o,s){let a=v(r,"x","conv2dTranspose"),i=v(e,"filter","conv2dTranspose");return Xc(t,a,i,n,o,"NHWC",s)}var vu=T({conv2dTranspose_:kW});function _W(r,e,t,n,o="NDHWC",s=[1,1,1]){let a=v(r,"x","conv3d"),i=v(e,"filter","conv3d"),l=a,u=!1;a.rank===4&&(u=!0,l=L(a,[1,a.shape[0],a.shape[1],a.shape[2],a.shape[3]])),E(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),E(i.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${i.rank}.`),E(l.shape[4]===i.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${i.shape[3]}.`),E(kr(t,s),()=>`Error in conv3D: Either strides or dilations must be 1. 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To get the original bytes, call tensor.bytes().")}}return e}dataSync(){this.throwIfDisposed();let e=Ri().readSync(this.dataId);if(this.dtype==="string")try{return e.map(t=>Bc(t))}catch(t){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}return e}async bytes(){this.throwIfDisposed();let e=await Ri().read(this.dataId);return this.dtype==="string"?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(Ri().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return Vc.print(this,e)}clone(){return this.throwIfDisposed(),Vc.clone(this)}toString(e=!1){let t=this.dataSync();return SI(t,this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),Vc.cast(this,e)}variable(e=!0,t,o){return this.throwIfDisposed(),Ri().makeVariable(this,e,t,o)}};Object.defineProperty(Ve,Symbol.hasInstance,{value:r=>!!r&&r.data!=null&&r.dataSync!=null&&r.throwIfDisposed!=null});function F(){return fm("Tensor",()=>Ve)}F();var rl=class extends Ve{constructor(e,t,o,n){super(e.shape,e.dtype,e.dataId,n);this.trainable=t,this.name=o}assign(e){if(e.dtype!==this.dtype)throw new Error(`dtype of the new value (${e.dtype}) and previous value (${this.dtype}) must match`);if(!jr(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);Ri().disposeTensor(this),this.dataId=e.dataId,Ri().incRef(this,null)}dispose(){Ri().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(rl,Symbol.hasInstance,{value:r=>r instanceof Ve&&r.assign!=null&&r.assign instanceof Function});var Mn={};Ke(Mn,{assertTypesMatch:()=>Wb,getTensorsInContainer:()=>bm,isTensorInList:()=>WB,makeTypesMatch:()=>Ge});var Lb;(function(r){r.R0="R0",r.R1="R1",r.R2="R2",r.R3="R3",r.R4="R4",r.R5="R5",r.R6="R6"})(Lb||(Lb={}));var zb;(function(r){r.float32="float32",r.int32="int32",r.bool="int32",r.complex64="complex64"})(zb||(zb={}));var Bb;(function(r){r.float32="float32",r.int32="int32",r.bool="bool",r.complex64="complex64"})(Bb||(Bb={}));var Vb;(function(r){r.float32="float32",r.int32="float32",r.bool="float32",r.complex64="complex64"})(Vb||(Vb={}));var Gb;(function(r){r.float32="complex64",r.int32="complex64",r.bool="complex64",r.complex64="complex64"})(Gb||(Gb={}));var GB={float32:Vb,int32:zb,bool:Bb,complex64:Gb};function dr(r,e){if(r==="string"||e==="string"){if(r==="string"&&e==="string")return"string";throw new Error(`Can not upcast ${r} with ${e}`)}return GB[r][e]}function fu(r){return dr(r,"int32")}function Ge(r,e){if(r.dtype===e.dtype)return[r,e];let t=dr(r.dtype,e.dtype);return[r.cast(t),e.cast(t)]}function Wb(r,e){A(r.dtype===e.dtype,()=>`The dtypes of the first(${r.dtype}) and second(${e.dtype}) input must match`)}function WB(r,e){return e.some(t=>t.id===r.id)}function bm(r){let e=[],t=new Set;return $I(r,e,t),e}function $I(r,e,t){if(r==null)return;if(r instanceof Ve){e.push(r);return}if(!jB(r))return;let o=r;for(let n in o){let s=o[n];t.has(s)||(t.add(s),$I(s,e,t))}}function jB(r){return Array.isArray(r)||typeof r=="object"}function jb(r){return r.kernelName!=null}var Ub=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}},du=class{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new Ub}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let o=e[t];if(await this.initializeBackend(o).success){await this.setBackend(o);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${this.backendName}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);if(this.backendInstance==null){let{name:e,asyncInit:t}=this.initializeBackendsAndReturnBest();if(t)throw new Error(`The highest priority backend '${e}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(e)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(e){if(!(e in this.registry))if(e in this.registryFactory){let{asyncInit:t}=this.initializeBackend(e);if(t)return null}else return null;return this.registry[e]}findBackendFactory(e){return e in this.registryFactory?this.registryFactory[e].factory:null}registerBackend(e,t,o=1){return e in this.registryFactory?(console.warn(`${e} backend was already registered. Reusing existing backend factory.`),!1):(this.registryFactory[e]={factory:t,priority:o},!0)}async setBackend(e){if(this.registryFactory[e]==null)throw new Error(`Backend name '${e}' not found in registry`);if(this.backendName=e,this.registry[e]==null){this.backendInstance=null;let{success:t,asyncInit:o}=this.initializeBackend(e);if(!(o?await t:t))return!1}return this.backendInstance=this.registry[e],this.setupRegisteredKernels(),this.profiler=new Pb(this.backendInstance),!0}setupRegisteredKernels(){hm(this.backendName).forEach(t=>{t.setupFunc!=null&&t.setupFunc(this.backendInstance)})}disposeRegisteredKernels(e){hm(e).forEach(o=>{o.disposeFunc!=null&&o.disposeFunc(this.registry[e])})}initializeBackend(e){let t=this.registryFactory[e];if(t==null)throw new Error(`Cannot initialize backend ${e}, no registration found.`);try{let o=t.factory();if(o&&!(o instanceof js)&&typeof o.then=="function"){let n=++this.pendingBackendInitId,s=o.then(a=>n<this.pendingBackendInitId?!1:(this.registry[e]=a,this.pendingBackendInit=null,!0)).catch(a=>(n<this.pendingBackendInitId||(this.pendingBackendInit=null,console.warn(`Initialization of backend ${e} failed`),console.warn(a.stack||a.message)),!1));return this.pendingBackendInit=s,{success:s,asyncInit:!0}}else return this.registry[e]=o,{success:!0,asyncInit:!1}}catch(o){return console.warn(`Initialization of backend ${e} failed`),console.warn(o.stack||o.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let o=e[t],{success:n,asyncInit:s}=this.initializeBackend(o);if(s||n)return{name:o,asyncInit:s}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let o=this.state.tensorInfo.get(t),n=o.backend,s=this.readSync(t),a=n.refCount(t);n.disposeData(t,!0),o.backend=e,e.move(t,s,o.shape,o.dtype,a),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let o=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");o=e}let n;return this.scopedRun(()=>this.startScope(o),()=>this.endScope(n),()=>(n=t(),n instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n))}scopedRun(e,t,o){e();try{let n=o();return t(),n}catch(n){throw t(),n}}nextTensorId(){return du.nextTensorId++}nextVariableId(){return du.nextVariableId++}clone(e){let t=E.runKernel(Fo,{x:e}),o={x:e},n=a=>({x:()=>{let i="float32",l={x:a},u={dtype:i};return E.runKernel($o,l,u)}}),s=[];return this.addTapeNode(this.state.activeScope.name,o,[t],n,s,{}),t}runKernel(e,t,o){if(!(Lc(e,this.backendName)!=null))throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:o})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,o){let n=this.backend.numDataIds(),s=0;o.forEach(l=>{s+=l.dtype==="complex64"?3:1});let a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=n-t-s-a;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,o=[],n=this.isTapeOn(),s=this.state.numBytes,a=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let l,u=jb(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(jb(e)){let{kernelName:d,inputs:h,attrs:g}=e;this.backendName==null&&this.backend;let x=Lc(d,this.backendName);A(x!=null,()=>`Cannot find registered kernel '${d}' for backend '${this.backendName}'`),i=()=>{let b=this.backend.numDataIds();l=x.kernelFunc({inputs:h,attrs:g,backend:this.backend});let w=Array.isArray(l)?l:[l];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(d,b,w);let k=w.map(_=>{if(_.rank!=null)return _;let{dataId:D,shape:T,dtype:R}=_;return this.makeTensorFromDataId(D,T,R)});if(n){let _=this.getTensorsForGradient(d,h,k);o=this.saveTensorsForBackwardMode(_)}return k}}else{let{forwardFunc:d}=e,h=g=>{!n||(o=g.map(x=>this.keep(this.clone(x))))};i=()=>{let g=this.backend.numDataIds();l=this.tidy(()=>d(this.backend,h));let x=Array.isArray(l)?l:[l];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(u,g,x),x}}let{inputs:c,attrs:p}=e,m=jb(e)?null:e.backwardsFunc,f;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(f=this.profiler.profileKernel(u,c,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(f),t=f.outputs)}),n&&this.addTapeNode(u,c,t,m,o,p),this.state.profiling&&this.state.activeProfile.kernels.push({name:u,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(d=>c[d]!=null?c[d].shape:null),outputShapes:t.map(d=>d.shape),kernelTimeMs:f.timeMs,extraInfo:f.extraInfo}),Array.isArray(l)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(o=>this.keep(this.clone(o)))}getTensorsForGradient(e,t,o){let n=Bh(e);if(n!=null){let s=n.inputsToSave||[],a=n.outputsToSave||[],i;n.saveAllInputs?(A(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(u=>t[u])):i=s.map(u=>t[u]);let l=o.filter((u,c)=>a[c]);return i.concat(l)}return[]}makeTensor(e,t,o,n){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");o=o||"float32",n=n||this.backend;let s=e;o==="string"&&is(e[0])&&(s=e.map(l=>tl(l)));let a=n.write(s,t,o),i=new Ve(t,o,a,this.nextTensorId());if(this.trackTensor(i,n),o==="string"){let l=this.state.tensorInfo.get(a),u=Tb(s);this.state.numBytes+=u-l.bytes,l.bytes=u}return i}makeTensorFromDataId(e,t,o,n){o=o||"float32";let s=new Ve(t,o,e,this.nextTensorId());return this.trackTensor(s,n),s}makeVariable(e,t=!0,o,n){o=o||this.nextVariableId().toString(),n!=null&&n!==e.dtype&&(e=e.cast(n));let s=new rl(e,t,o,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 o=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(o=e.size*Lh(e.dtype)),this.state.numBytes+=o,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:o})),e instanceof rl||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 o=e.size*Lh(e.dtype);this.state.numBytes-=o}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,o=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(n=>n.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-o;for(let n of 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+    ${n} and ${e}  for depthToSpace with input shape
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p={x:u,filter:l},m={strides:t,pad:n,dataFormat:o,dilations:s,dimRoundingMode:a},f=D.runKernel(to,p,m);return c?L(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var Is=T({depthwiseConv2d_:DW});function $W(r){let t={x:v(r,"x","diag")};return D.runKernel(Xl,t)}var RW=T({diag_:$W});function FW(r,e,t,n,o=[1,1],s="NHWC"){let a=v(r,"x","dilation2d"),i=v(e,"filter","dilation2d");E(a.rank===3||a.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${a.rank}.`),E(i.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${i.rank}.`),E(s==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${s}`);let l=a,u=!1;a.rank===3&&(l=L(a,[1,a.shape[0],a.shape[1],a.shape[2]]),u=!0);let c={x:l,filter:i},p={strides:t,pad:n,dilations:o},m=D.runKernel(sa,c,p);return u?L(m,[m.shape[1],m.shape[2],m.shape[3]]):m}var Fm=T({dilation2d_:FW});function OW(r,e){let t=r.length,n=[];for(let o=0;o<t;o++){let s=t-1-o,a=r[s]||1;(e[e.length-1-o]||1)>1&&a===1&&n.unshift(s)}return n}function _t(r,e){let t=[];for(let n=0;n<e.length;n++){let o=r[r.length-n-1],s=e.length-n-1,a=e[s];(o==null||o===1&&a>1)&&t.unshift(s)}return t}function Be(r,e){let t=[],n=Math.max(r.length,e.length);for(let o=0;o<n;o++){let s=r[r.length-o-1];s==null&&(s=1);let a=e[e.length-o-1];if(a==null&&(a=1),s===1)t.unshift(a);else if(a===1)t.unshift(s);else if(s!==a){let i=`Operands could not be broadcast together with shapes ${r} and ${e}.`;throw Error(i)}else t.unshift(s)}return t}function PW(r,e){let t=v(r,"a","equal"),n=v(e,"b","equal");[t,n]=Ge(t,n),Be(t.shape,n.shape);let o={a:t,b:n};return D.runKernel(si,o)}var vn=T({equal_:PW});function MW(r,e,t){let n=v(e,"a","where"),o=v(t,"b","where"),s=v(r,"condition","where","bool"),a=Be(n.shape,o.shape),i=al(n,a),l=al(o,a);s.rank===1&&E(s.shape[0]===n.shape[0],()=>"The first dimension of `a` must match the size of `condition`."),s.rank!==1&&Ct(s.shape,l.shape,"Error in where: 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We(t,a)}}var Aw=T({dot_:BW});function VW(r){let t={x:v(r,"x","elu")};return D.runKernel(ni,t)}var Ns=T({elu_:VW});function GW(r){let e=v(r,"x","erf");E(e.dtype==="int32"||e.dtype==="float32",()=>"Input dtype must be `int32` or `float32`."),e.dtype==="int32"&&(e=oe(e,"float32"));let t={x:e};return D.runKernel(oi,t)}var Pm=T({erf_:GW});function WW(r){let t={x:v(r,"x","exp")};return D.runKernel(no,t)}var Zt=T({exp_:WW});function jW(r,e=0){let t=v(r,"x","expandDims","string_or_numeric");E(e<=t.rank,()=>"Axis must be <= rank of the tensor");let n={input:t},o={dim:e};return D.runKernel(us,n,o)}var ar=T({expandDims_:jW});function UW(r){let t={x:v(r,"x","expm1")};return D.runKernel(ii,t)}var Mm=T({expm1_:UW});function HW(r,e){let t=v(r,"x","tile","string_or_numeric");E(t.rank===e.length,()=>`Error in transpose: rank of input ${t.rank} must match length of reps ${e}.`);let n={x:t},o={reps:e};return D.runKernel(kn,n,o)}var zn=T({tile_:HW});function qW(r,e,t,n="float32"){e==null&&(e=r);let 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s=oS(o,t),a=1-e,i=me(Ss(ee(Es(s,0,1,"float32",n),a)),a);return P(o,i)}var tk=T({dropout_:bU});function rk(r){return Math.floor(Math.pow(2,Math.ceil(Math.log(r)/Math.log(2))))}function rf(r,e,t){let n=1-r%2,o=new Float32Array(r);for(let s=0;s<r;++s){let a=2*Math.PI*s/(r+n-1);o[s]=e-t*Math.cos(a)}return Gt(o,"float32")}async function wU(r,e,t=1){let n=v(r,"predictions","inTopK"),o=v(e,"targets","inTopK");E(n.rank>1,()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${n.rank}`),E(n.rank-1===o.rank,()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${n.rank} and targets rank ${o.rank}`),Ct(n.shape.slice(0,n.shape.length-1),o.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");let s=n.shape[n.shape.length-1];E(t>0&&t<=s,()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${s}), but got ${t}`);let a=await n.data(),i=await o.data(),[l,u]=[a.length/s,s],c=Sb("bool",l);for(let p=0;p<l;p++){let m=p*u,f=a.subarray(m,m+u),d=[];for(let h=0;h<f.length;h++)d.push({value:f[h],index:h});d.sort((h,g)=>g.value-h.value),c[p]=0;for(let h=0;h<t;h++)if(d[h].index===i[p]){c[p]=1;break}}return r!==n&&n.dispose(),e!==o&&o.dispose(),Rr(c,o.shape,"bool")}var kU=wU;var Go={};Ke(Go,{conv2d:()=>CU,depthwiseConv2d:()=>TU,matMul:()=>EU});function _U(r,e,t,n,o,s="NHWC",a){let i=r;r.rank===3&&(i=L(r,[1,r.shape[0],r.shape[1],r.shape[2]]));let l=e;l.rank===3&&(l=L(e,[1,e.shape[0],e.shape[1],e.shape[2]])),E(i.rank===4,()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${i.shape}.`),E(l.rank===4,()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${l.shape}.`),E(t.length===4,()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${t}.`);let u=s==="NHWC"?i.shape[3]:i.shape[1],c=s==="NHWC"?l.shape[3]:l.shape[1];E(u===t[2],()=>`Error in conv2dDerFilter: depth of input ${u}) must match input depth 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vU({x:r,filter:e,strides:t,pad:n,dataFormat:o="NHWC",dilations:s=[1,1],dimRoundingMode:a,bias:i,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(l=l||"linear",Uu(D.state.gradientDepth,l)===!1){let _=Kr(r,e,t,n,o,s,a);return i!=null&&(_=ee(_,i)),ju(_,l,u,c)}let p=v(r,"x","conv2d"),m=v(e,"filter","conv2d"),f=p,d=!1;p.rank===3&&(d=!0,f=L(p,[1,p.shape[0],p.shape[1],p.shape[2]])),E(f.rank===4,()=>`Error in fused conv2d: input must be rank 4, but got rank ${f.rank}.`),E(m.rank===4,()=>`Error in fused conv2d: filter must be rank 4, but got rank ${m.rank}.`),a!=null&&E(nt(n),()=>`Error in fused conv2d: pad must be an integer when using, dimRoundingMode ${a} but got pad ${n}.`),E(f.shape[3]===m.shape[2],()=>`Error in conv2d: depth of input (${f.shape[3]}) must match input depth for filter ${m.shape[2]}.`),E(kr(t,s),()=>`Error in conv2D: Either strides or dilations must be 1. 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a=v(r,"boxes","nonMaxSuppression"),i=v(e,"scores","nonMaxSuppression"),l=Wo(a,i,t,n,o,null),u=l.maxOutputSize,c=l.iouThreshold,p=l.scoreThreshold,m={boxes:a,scores:i},f={maxOutputSize:u,iouThreshold:c,scoreThreshold:p,padToMaxOutputSize:s},d=D.runKernel(wi,m,f);return{selectedIndices:d[0],validOutputs:d[1]}}var gS=T({nonMaxSuppressionPadded_:qU});async function KU(r,e,t,n=.5,o=Number.NEGATIVE_INFINITY,s=!1){let a=v(r,"boxes","nonMaxSuppressionAsync"),i=v(e,"scores","nonMaxSuppressionAsync"),l=Wo(a,i,t,n,o,null),u=l.maxOutputSize,c=l.iouThreshold,p=l.scoreThreshold,[m,f]=await Promise.all([a.data(),i.data()]),{selectedIndices:d,validOutputs:h}=sk(m,f,u,c,p,s);return a!==r&&a.dispose(),i!==e&&i.dispose(),{selectedIndices:Gt(d,"int32"),validOutputs:le(h,"int32")}}var xS=KU;function XU(r,e,t=!1,n=!1){let o=v(r,"images","resizeBilinear");E(o.rank===3||o.rank===4,()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${o.rank}.`),E(e.length===2,()=>`Error in resizeBilinear: new 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s=o,a=!1;o.rank===3&&(a=!0,s=L(o,[1,o.shape[0],o.shape[1],o.shape[2]]));let[]=e,i={images:s},l={alignCorners:t,halfPixelCenters:n,size:e},u=D.runKernel(pa,i,l);return a?L(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var xg=T({resizeNearestNeighbor_:YU});function ZU(r,e,t="nearest",n="constant",o=0,s){let a=v(r,"image","transform","float32"),i=v(e,"transforms","transform","float32");E(a.rank===4,()=>`Error in transform: image must be rank 4,but got rank ${a.rank}.`),E(i.rank===2&&(i.shape[0]===a.shape[0]||i.shape[0]===1)&&i.shape[1]===8,()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),E(s==null||s.length===2,()=>`Error in transform: outputShape must be [height, width] or null, but got ${s}.`);let l={image:a,transforms:i},u={interpolation:t,fillMode:n,fillValue:o,outputShape:s};return D.runKernel(cu,l,u)}var yS=T({transform_:ZU});function JU(r,e,t){E(e%1==0,()=>`bandPart(): numLower must be an integer, got ${e}.`),E(t%1==0,()=>`bandPart(): numUpper must be an integer, got ${t}.`);let n=v(r,"a","bandPart");E(n.rank>=2,()=>`bandPart(): Rank must be at least 2, got ${n.rank}.`);let o=n.shape,[s,a]=n.shape.slice(-2);if(!(e<=s))throw new Error(`bandPart(): numLower (${e}) must not be greater than the number of rows (${s}).`);if(!(t<=a))throw new Error(`bandPart(): numUpper (${t}) must not be greater than the number of columns (${a}).`);e<0&&(e=s),t<0&&(t=a);let i=L(Qc(0,s,1,"int32"),[-1,1]),l=Qc(0,a,1,"int32"),u=ce(i,l),c=hr(Bn(u,le(+e,"int32")),an(u,le(-t,"int32"))),p=gt([s,a],n.dtype);return L(Vt(pr(L(n,[-1,s,a])).map(m=>$t(c,m,p))),o)}var bS=T({bandPart_:JU});function QU(r){let e;if(Array.isArray(r)){e=!1,E(r!=null&&r.length>0,()=>"Gram-Schmidt process: input must not be null, undefined, or empty");let o=r[0].shape[0];for(let s=1;s<r.length;++s)E(r[s].shape[0]===o,()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${r[s].shape[0]} vs. ${o})`)}else e=!0,r=cr(r,r.shape[0],0).map(o=>Cn(o,[0]));E(r.length<=r[0].shape[0],()=>`Gram-Schmidt: 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o=v(r,"labels","hingeLoss"),s=v(e,"predictions","hingeLoss"),a=null;t!=null&&(a=v(t,"weights","hingeLoss")),Ct(o.shape,s.shape,"Error in hingeLoss: ");let i=le(1);o=ce(P(le(2),o),i);let l=Sr(ce(i,P(o,s)));return Tr(l,a,n)}var IS=T({hingeLoss_:oH});function sH(r,e,t,n=1,o=Wt.SUM_BY_NONZERO_WEIGHTS){let s=v(r,"labels","huberLoss"),a=v(e,"predictions","huberLoss"),i=null;t!=null&&(i=v(t,"weights","huberLoss")),Ct(s.shape,a.shape,"Error in huberLoss: ");let l=le(n),u=Nt(ce(a,s)),c=As(u,l),p=ce(u,c),m=ee(P(le(.5),Oe(c)),P(l,p));return Tr(m,i,o)}var NS=T({huberLoss_:sH});function iH(r,e,t,n=1e-7,o=Wt.SUM_BY_NONZERO_WEIGHTS){let s=v(r,"labels","logLoss"),a=v(e,"predictions","logLoss"),i=null;t!=null&&(i=v(t,"weights","logLoss")),Ct(s.shape,a.shape,"Error in logLoss: ");let l=le(1),u=le(n),c=He(P(s,lr(ee(a,u)))),p=P(ce(l,s),lr(ee(ce(l,a),u))),m=ce(c,p);return Tr(m,i,o)}var SS=T({logLoss_:iH});function aH(r,e,t,n=Wt.SUM_BY_NONZERO_WEIGHTS){let o=v(r,"labels","meanSquaredError"),s=v(e,"predictions","meanSquaredError"),a=null;t!=null&&(a=v(t,"weights","meanSquaredError")),Ct(o.shape,s.shape,"Error in meanSquaredError: ");let i=zu(o,s);return Tr(i,a,n)}var TS=T({meanSquaredError_:aH});function lH(r,e){let t=v(r,"labels","sigmoidCrossEntropyWithLogits"),n=v(e,"logits","sigmoidCrossEntropyWithLogits");Ct(t.shape,n.shape,"Error in sigmoidCrossEntropyWithLogits: ");let o=Sr(n),s=P(n,t),a=Tu(Zt(He(Nt(n))));return ee(ce(o,s),a)}function uH(r,e,t,n=0,o=Wt.SUM_BY_NONZERO_WEIGHTS){let s=v(r,"multiClassLabels","sigmoidCrossEntropy"),a=v(e,"logits","sigmoidCrossEntropy"),i=null;if(t!=null&&(i=v(t,"weights","sigmoidCrossEntropy")),Ct(s.shape,a.shape,"Error in sigmoidCrossEntropy: "),n>0){let u=le(n),c=le(1),p=le(.5);s=ee(P(s,ce(c,u)),P(p,u))}let l=lH(s,a);return Tr(l,i,o)}var AS=T({sigmoidCrossEntropy_:uH});function cH(r,e,t=-1){if(t===-1&&(t=e.rank-1),t!==e.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet 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Labels / logits was rank ${e.rank} and dim was ${t}`);return Xr((o,s,a)=>{let l=Bm(s,[t],!0),u=ce(oe(s,"float32"),l);a([o,u]);let c=He(P(u,o));return{value:ge(c,[t]),gradFunc:(f,d)=>{let[h,g]=d,x=Bo(f.shape,[t]);return[P(L(f,x),ce(oe(h,"float32"),Zt(g))),P(L(f,x),ce(Zt(g),oe(h,"float32")))]}}})(r,e)}function pH(r,e,t,n=0,o=Wt.SUM_BY_NONZERO_WEIGHTS){let s=v(r,"onehotLabels","softmaxCrossEntropy"),a=v(e,"logits","softmaxCrossEntropy"),i=null;if(t!=null&&(i=v(t,"weights","softmaxCrossEntropy")),Ct(s.shape,a.shape,"Error in softmaxCrossEntropy: "),n>0){let u=le(n),c=le(1),p=le(s.shape[1]);s=ee(P(s,ce(c,u)),me(u,p))}let l=cH(s,a);return Tr(l,i,o)}var ES=T({softmaxCrossEntropy_:pH});var mH={fft:Ea,ifft:Mi,rfft:Da,irfft:Lu},fH={hammingWindow:sS,hannWindow:dg,frame:hg,stft:iS},$s={flipLeftRight:lS,resizeNearestNeighbor:xg,resizeBilinear:gg,rotateWithOffset:uS,cropAndResize:aS,nonMaxSuppression:cS,nonMaxSuppressionAsync:fS,nonMaxSuppressionWithScore:dS,nonMaxSuppressionWithScoreAsync:hS,nonMaxSuppressionPadded:gS,nonMaxSuppressionPaddedAsync:xS,transform:yS},ak={bandPart:bS,gramSchmidt:wS,qr:_S},dH={absoluteDifference:vS,computeWeightedLoss:Tr,cosineDistance:CS,hingeLoss:IS,huberLoss:NS,logLoss:SS,meanSquaredError:TS,sigmoidCrossEntropy:AS,softmaxCrossEntropy:ES};var Pr=class extends tg{minimize(e,t=!1,n){let{value:o,grads:s}=this.computeGradients(e,n);if(n!=null){let a=n.map(i=>({name:i.name,tensor:s[i.name]}));this.applyGradients(a)}else this.applyGradients(s);return Ae(s),t?o:(o.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return ig(e,t)}dispose(){this.iterations_!=null&&Ae(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:le(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 ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(Pr,Symbol.hasInstance,{value:r=>r.minimize!=null&&r.computeGradients!=null&&r.applyGradients!=null});var np=class extends Pr{constructor(e,t,n=null){super();this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],n==null&&(this.epsilon=D.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,o)=>{let 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l=ee(i,Oe(a));i.assign(l);let u=ee(P(me(a,xt(ee(l,D.backend.epsilon()))),-this.learningRate),s);s.assign(u)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Ae(this.accumulatedGrads.map(e=>e.variable))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulatedGrads=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}};op.className="Adagrad";sn(op);var sp=class extends Pr{constructor(e,t,n,o=null){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=o,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],G(()=>{this.accBeta1=le(t).variable(),this.accBeta2=le(n).variable()}),o==null&&(this.epsilon=D.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);G(()=>{let n=ce(1,this.accBeta1),o=ce(1,this.accBeta2);t.forEach((s,a)=>{let i=D.registeredVariables[s],l=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:G(()=>Ce(i).variable(l))}),this.accumulatedSecondMoment[a]==null&&(this.accumulatedSecondMoment[a]={originalName:`${s}/v`,variable:G(()=>Ce(i).variable(l))});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,p=this.accumulatedSecondMoment[a].variable,m=ee(P(c,this.beta1),P(u,1-this.beta1)),f=ee(P(p,this.beta2),P(Oe(u),1-this.beta2)),d=me(m,n),h=me(f,o);c.assign(m),p.assign(f);let g=ee(P(me(d,ee(xt(h),this.epsilon)),-this.learningRate),i);i.assign(g)}),this.accBeta1.assign(P(this.accBeta1,this.beta1)),this.accBeta2.assign(P(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&Ae(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&Ae(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),G(()=>{this.accBeta1.assign(Or(this.beta1,this.iterations_+1)),this.accBeta2.assign(Or(this.beta2,this.iterations_+1))});let t=e.length/2,n=!1;this.accumulatedFirstMoment=e.slice(0,t).map(o=>({originalName:o.name,variable:o.tensor.variable(n)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(o=>({originalName:o.name,variable:o.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)}};sp.className="Adam";sn(sp);var ip=class extends Pr{constructor(e,t,n,o=null,s=0){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=o,this.decay=s,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],G(()=>{this.iteration=le(0).variable(),this.accBeta1=le(t).variable()}),o==null&&(this.epsilon=D.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);G(()=>{let n=ce(1,this.accBeta1),o=me(-this.learningRate,ee(P(this.iteration,this.decay),1));t.forEach((s,a)=>{let i=D.registeredVariables[s],l=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:Ce(i).variable(l)}),this.accumulatedWeightedInfNorm[a]==null&&(this.accumulatedWeightedInfNorm[a]={originalName:`${s}/v`,variable:Ce(i).variable(l)});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,p=this.accumulatedWeightedInfNorm[a].variable,m=ee(P(c,this.beta1),P(u,1-this.beta1)),f=P(p,this.beta2),d=Nt(u),h=Yr(f,d);c.assign(m),p.assign(h);let g=ee(P(me(o,n),me(m,ee(h,this.epsilon))),i);i.assign(g)}),this.iteration.assign(ee(this.iteration,1)),this.accBeta1.assign(P(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Ae(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Ae(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)}};ip.className="Adamax";sn(ip);var ul=class extends Pr{constructor(e){super();this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,o)=>{let s=Array.isArray(e)?e[o].tensor:e[n];if(s==null)return;let a=D.registeredVariables[n];G(()=>{let i=ee(P(this.c,s),a);a.assign(i)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Dt(le(-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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t=this.centered?e.length/3:e.length/2,n=!1;this.accumulatedMeanSquares=e.slice(0,t).map(o=>({originalName:o.name,variable:o.tensor.variable(n)})),this.accumulatedMoments=e.slice(t,t*2).map(o=>({originalName:o.name,variable:o.tensor.variable(n)})),this.centered&&(this.accumulatedMeanGrads=e.slice(t*2,t*3).map(o=>({originalName:o.name,variable:o.tensor.variable(n)})))}getConfig(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}}static fromConfig(e,t){return new e(t.learningRate,t.decay,t.momentum,t.epsilon,t.centered)}};lp.className="RMSProp";sn(lp);var $a=class{static sgd(e){return new ul(e)}static momentum(e,t,n=!1){return new ap(e,t,n)}static rmsprop(e,t=.9,n=0,o=null,s=!1){return new lp(e,t,n,o,s)}static adam(e=.001,t=.9,n=.999,o=null){return new sp(e,t,n,o)}static adadelta(e=.001,t=.95,n=null){return new np(e,t,n)}static adamax(e=.002,t=.9,n=.999,o=null,s=0){return new ip(e,t,n,o,s)}static 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n=v(r,"labels","hingeLoss"),s=v(e,"predictions","hingeLoss"),a=null;t!=null&&(a=v(t,"weights","hingeLoss")),vt(n.shape,s.shape,"Error in hingeLoss: ");let i=le(1);n=ce(P(le(2),n),i);let l=Sr(ce(i,P(n,s)));return Tr(l,a,o)}var xS=S({hingeLoss_:OU});function PU(r,e,t,o=1,n=Gt.SUM_BY_NONZERO_WEIGHTS){let s=v(r,"labels","huberLoss"),a=v(e,"predictions","huberLoss"),i=null;t!=null&&(i=v(t,"weights","huberLoss")),vt(s.shape,a.shape,"Error in huberLoss: ");let l=le(o),u=It(ce(a,s)),c=As(u,l),p=ce(u,c),m=ee(P(le(.5),Oe(c)),P(l,p));return Tr(m,i,n)}var yS=S({huberLoss_:PU});function MU(r,e,t,o=1e-7,n=Gt.SUM_BY_NONZERO_WEIGHTS){let s=v(r,"labels","logLoss"),a=v(e,"predictions","logLoss"),i=null;t!=null&&(i=v(t,"weights","logLoss")),vt(s.shape,a.shape,"Error in logLoss: ");let l=le(1),u=le(o),c=He(P(s,lr(ee(a,u)))),p=P(ce(l,s),lr(ee(ce(l,a),u))),m=ce(c,p);return Tr(m,i,n)}var bS=S({logLoss_:MU});function LU(r,e,t,o=Gt.SUM_BY_NONZERO_WEIGHTS){let 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supported. Labels / logits was rank ${e.rank} and dim was ${t}`);return Xr((n,s,a)=>{let l=zm(s,[t],!0),u=ce(ne(s,"float32"),l);a([n,u]);let c=He(P(u,n));return{value:ge(c,[t]),gradFunc:(f,d)=>{let[h,g]=d,x=Bn(f.shape,[t]);return[P(L(f,x),ce(ne(h,"float32"),Zt(g))),P(L(f,x),ce(Zt(g),ne(h,"float32")))]}}})(r,e)}function GU(r,e,t,o=0,n=Gt.SUM_BY_NONZERO_WEIGHTS){let s=v(r,"onehotLabels","softmaxCrossEntropy"),a=v(e,"logits","softmaxCrossEntropy"),i=null;if(t!=null&&(i=v(t,"weights","softmaxCrossEntropy")),vt(s.shape,a.shape,"Error in softmaxCrossEntropy: "),o>0){let u=le(o),c=le(1),p=le(s.shape[1]);s=ee(P(s,ce(c,u)),me(u,p))}let l=VU(s,a);return Tr(l,i,n)}var _S=S({softmaxCrossEntropy_:GU});var WU={fft:Ea,ifft:Mi,rfft:Da,irfft:Lu},jU={hammingWindow:ZN,hannWindow:mg,frame:fg,stft:JN},$s={flipLeftRight:eS,resizeNearestNeighbor:hg,resizeBilinear:dg,rotateWithOffset:tS,cropAndResize:QN,nonMaxSuppression:rS,nonMaxSuppressionAsync:sS,nonMaxSuppressionWithScore:iS,nonMaxSuppressionWithScoreAsync:aS,nonMaxSuppressionPadded:lS,nonMaxSuppressionPaddedAsync:uS,transform:cS},ik={bandPart:pS,gramSchmidt:mS,qr:dS},UU={absoluteDifference:hS,computeWeightedLoss:Tr,cosineDistance:gS,hingeLoss:xS,huberLoss:yS,logLoss:bS,meanSquaredError:wS,sigmoidCrossEntropy:kS,softmaxCrossEntropy:_S};var Pr=class extends eg{minimize(e,t=!1,o){let{value:n,grads:s}=this.computeGradients(e,o);if(o!=null){let a=o.map(i=>({name:i.name,tensor:s[i.name]}));this.applyGradients(a)}else this.applyGradients(s);return Ae(s),t?n:(n.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return sg(e,t)}dispose(){this.iterations_!=null&&Ae(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:le(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 ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(Pr,Symbol.hasInstance,{value:r=>r.minimize!=null&&r.computeGradients!=null&&r.applyGradients!=null});var rp=class extends Pr{constructor(e,t,o=null){super();this.learningRate=e,this.rho=t,this.epsilon=o,this.accumulatedGrads=[],this.accumulatedUpdates=[],o==null&&(this.epsilon=E.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=E.registeredVariables[o],a=!1;this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${o}/accum_grad`,variable:V(()=>Ce(s).variable(a))}),this.accumulatedUpdates[n]==null&&(this.accumulatedUpdates[n]={originalName:`${o}/accum_var`,variable:V(()=>Ce(s).variable(a))});let i=Array.isArray(e)?e[n].tensor:e[o];if(i==null)return;let l=this.accumulatedGrads[n].variable,u=this.accumulatedUpdates[n].variable;V(()=>{let c=ee(P(l,this.rho),P(Oe(i),1-this.rho)),p=P(me(gt(ee(u,this.epsilon)),gt(ee(l,this.epsilon))),i),m=ee(P(u,this.rho),P(Oe(p),1-this.rho));l.assign(c),u.assign(m);let f=ee(P(p,-this.learningRate),s);s.assign(f)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(Ae(this.accumulatedGrads.map(e=>e.variable)),Ae(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,o=!1;this.accumulatedGrads=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.accumulatedUpdates=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(o)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};rp.className="Adadelta";so(rp);var op=class extends Pr{constructor(e,t=.1){super();this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=E.registeredVariables[o];if(this.accumulatedGrads[n]==null){let l=!1;this.accumulatedGrads[n]={originalName:`${o}/accumulator`,variable:V(()=>va(s.shape,this.initialAccumulatorValue).variable(l))}}let a=Array.isArray(e)?e[n].tensor:e[o];if(a==null)return;let i=this.accumulatedGrads[n].variable;V(()=>{let l=ee(i,Oe(a));i.assign(l);let u=ee(P(me(a,gt(ee(l,E.backend.epsilon()))),-this.learningRate),s);s.assign(u)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Ae(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(o=>({originalName:o.name,variable:o.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}};op.className="Adagrad";so(op);var np=class extends Pr{constructor(e,t,o,n=null){super();this.learningRate=e,this.beta1=t,this.beta2=o,this.epsilon=n,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],V(()=>{this.accBeta1=le(t).variable(),this.accBeta2=le(o).variable()}),n==null&&(this.epsilon=E.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);V(()=>{let o=ce(1,this.accBeta1),n=ce(1,this.accBeta2);t.forEach((s,a)=>{let i=E.registeredVariables[s],l=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:V(()=>Ce(i).variable(l))}),this.accumulatedSecondMoment[a]==null&&(this.accumulatedSecondMoment[a]={originalName:`${s}/v`,variable:V(()=>Ce(i).variable(l))});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,p=this.accumulatedSecondMoment[a].variable,m=ee(P(c,this.beta1),P(u,1-this.beta1)),f=ee(P(p,this.beta2),P(Oe(u),1-this.beta2)),d=me(m,o),h=me(f,n);c.assign(m),p.assign(f);let g=ee(P(me(d,ee(gt(h),this.epsilon)),-this.learningRate),i);i.assign(g)}),this.accBeta1.assign(P(this.accBeta1,this.beta1)),this.accBeta2.assign(P(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&Ae(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&Ae(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),V(()=>{this.accBeta1.assign(Or(this.beta1,this.iterations_+1)),this.accBeta2.assign(Or(this.beta2,this.iterations_+1))});let t=e.length/2,o=!1;this.accumulatedFirstMoment=e.slice(0,t).map(n=>({originalName:n.name,variable:n.tensor.variable(o)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(n=>({originalName:n.name,variable:n.tensor.variable(o)}))}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)}};np.className="Adam";so(np);var sp=class extends Pr{constructor(e,t,o,n=null,s=0){super();this.learningRate=e,this.beta1=t,this.beta2=o,this.epsilon=n,this.decay=s,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],V(()=>{this.iteration=le(0).variable(),this.accBeta1=le(t).variable()}),n==null&&(this.epsilon=E.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);V(()=>{let o=ce(1,this.accBeta1),n=me(-this.learningRate,ee(P(this.iteration,this.decay),1));t.forEach((s,a)=>{let i=E.registeredVariables[s],l=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${s}/m`,variable:Ce(i).variable(l)}),this.accumulatedWeightedInfNorm[a]==null&&(this.accumulatedWeightedInfNorm[a]={originalName:`${s}/v`,variable:Ce(i).variable(l)});let u=Array.isArray(e)?e[a].tensor:e[s];if(u==null)return;let c=this.accumulatedFirstMoment[a].variable,p=this.accumulatedWeightedInfNorm[a].variable,m=ee(P(c,this.beta1),P(u,1-this.beta1)),f=P(p,this.beta2),d=It(u),h=Yr(f,d);c.assign(m),p.assign(h);let g=ee(P(me(n,o),me(m,ee(h,this.epsilon))),i);i.assign(g)}),this.iteration.assign(ee(this.iteration,1)),this.accBeta1.assign(P(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Ae(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Ae(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)}};sp.className="Adamax";so(sp);var ul=class extends Pr{constructor(e){super();this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=Array.isArray(e)?e[n].tensor:e[o];if(s==null)return;let a=E.registeredVariables[o];V(()=>{let i=ee(P(this.c,s),a);a.assign(i)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Et(le(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does not have settable weights.")}getConfig(){return{learningRate:this.learningRate}}static fromConfig(e,t){return new e(t.learningRate)}};ul.className="SGD";so(ul);var ip=class extends ul{constructor(e,t,o=!1){super(e);this.learningRate=e,this.momentum=t,this.useNesterov=o,this.accumulations=[],this.m=le(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(o=>o.name):Object.keys(e)).forEach((o,n)=>{let s=E.registeredVariables[o];if(this.accumulations[n]==null){let l=!1;this.accumulations[n]={originalName:`${o}/momentum`,variable:V(()=>Ce(s).variable(l))}}let a=this.accumulations[n].variable,i=Array.isArray(e)?e[n].tensor:e[o];i!=null&&V(()=>{let l,u=ee(P(this.m,a),i);this.useNesterov?l=ee(P(this.c,ee(i,P(u,this.m))),s):l=ee(P(this.c,u),s),a.assign(u),s.assign(l)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&Ae(this.accumulations.map(e=>e.variable))}setMomentum(e){this.momentum=e}async getWeights(){return[await 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GT={kernelName:Bl,backendName:"cpu",kernelFunc:Tq};function Aq(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,input:s}=e,a=s;te([o,s],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=n,c=S.computePool2DInfo(a.shape,i,l,1,u),p=c.strideHeight,m=c.strideWidth,f=c.filterHeight,d=c.filterWidth,h=c.dilationHeight,g=c.dilationWidth,x=c.effectiveFilterHeight,w=c.effectiveFilterWidth,b=w-1-c.padInfo.left,k=x-1-c.padInfo.top,_=ve(a.shape,"float32"),A=1/(f*d),N=t.data.get(o.dataId).values,$=ve(o.shape,"float32",N);for(let F=0;F<c.batchSize;++F)for(let M=0;M<c.inChannels;++M)for(let V=0;V<c.inHeight;++V)for(let W=0;W<c.inWidth;++W){let U=V-k,H=W-b,q=0;for(let X=0;X<x;X+=h){let ne=(U+X)/p;if(!(ne<0||ne>=c.outHeight||Math.floor(ne)!==ne))for(let Y=0;Y<w;Y+=g){let re=(H+Y)/m;if(re<0||re>=c.outWidth||Math.floor(re)!==re)continue;q+=$.get(F,ne,re,M)}}_.set(q*A,F,V,W,M)}return t.makeTensorInfo(_.shape,_.dtype,_.values)}var WT={kernelName:zl,backendName:"cpu",kernelFunc:Aq};function 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t.makeTensorInfo(o.shape,o.dtype,h)}var jT={kernelName:io,backendName:"cpu",kernelFunc:Eq};function Dq(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{blockShape:s,crops:a}=n;te([o],"batchToSpaceND");let i=s.reduce((x,w)=>x*w),l=S.getReshaped(o.shape,s,i),u=S.getPermuted(l.length,s.length),c=S.getReshapedPermuted(o.shape,s,i),p=S.getSliceBeginCoords(a,s.length),m=S.getSliceSize(c,a,s.length),f=Qe({inputs:{x:o},backend:t,attrs:{shape:l}}),d=rr({inputs:{x:f},backend:t,attrs:{perm:u}}),h=Qe({inputs:{x:d},backend:t,attrs:{shape:c}}),g=Ko({inputs:{x:h},backend:t,attrs:{begin:p,size:m}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(h),g}var UT={kernelName:ra,backendName:"cpu",kernelFunc:Dq};function $q(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,weights:s}=e,{size:a}=n,i=t.data.get(o.dataId).values,l=t.data.get(s.dataId).values,u=of(i,l,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,u)}var HT={kernelName:Vl,backendName:"cpu",kernelFunc:$q};var Rq=$e(Rn,(r,e)=>{let t=e;return r>t.clipValueMax?t.clipValueMax:r<t.clipValueMin?t.clipValueMin:r}),qT={kernelName:Rn,backendName:"cpu",kernelFunc:Rq};var Fq=r=>{let{x:e}=r.inputs,t=r.backend,n=new Float32Array(y.sizeFromShape(e.shape)),o=t.data.get(e.dataId),s=o.complexTensorInfos.real,a=o.complexTensorInfos.imag,i=t.data.get(s.dataId).values,l=t.data.get(a.dataId).values;for(let u=0;u<i.length;u++){let c=i[u],p=l[u];n[u]=Math.hypot(c,p)}return t.makeOutput(n,e.shape,"float32")},KT={kernelName:na,backendName:"cpu",kernelFunc:Fq};function zi(r){let{inputs:e,backend:t}=r,{input:n}=e,o=t.data.get(n.dataId).complexTensorInfos.imag,s=t.data.get(o.dataId).values;return t.makeTensorInfo(o.shape,o.dtype,s)}var XT={kernelName:Ql,backendName:"cpu",kernelFunc:zi};function pl(r){let{inputs:e,backend:t,attrs:n}=r,{axis:o}=n,s=y.parseAxisParam(o,e[0].shape)[0],a=S.computeOutShape(e.map(h=>h.shape),s);if(y.sizeFromShape(a)===0)return t.makeTensorInfo(a,e[0].dtype,[]);let i=e.filter(h=>y.sizeFromShape(h.shape)>0);if(i.length===1)return Er({inputs:{x:i[0]},backend:t});let l=i.map(h=>h.shape);if(S.assertParamsConsistent(l,s),i[0].dtype==="complex64"){let h=i.map(k=>jo({inputs:{input:k},backend:t})),g=i.map(k=>zi({inputs:{input:k},backend:t})),x=pl({inputs:h,backend:t,attrs:{axis:s}}),w=pl({inputs:g,backend:t,attrs:{axis:s}}),b=mr({inputs:{real:x,imag:w},backend:t});return h.forEach(k=>t.disposeIntermediateTensorInfo(k)),g.forEach(k=>t.disposeIntermediateTensorInfo(k)),t.disposeIntermediateTensorInfo(x),t.disposeIntermediateTensorInfo(w),b}let u=i.map(h=>{let g=y.sizeFromShape(h.shape.slice(s));return Qe({inputs:{x:h},backend:t,attrs:{shape:[-1,g]}})}),c=u.map(h=>({vals:t.data.get(h.dataId).values,shape:h.shape}));a=S.computeOutShape(u.map(h=>h.shape),1);let p=u[0].shape[0]===1,m=sf(c,a,e[0].dtype,p),f=S.computeOutShape(i.map(h=>h.shape),s),d=t.makeTensorInfo(f,e[0].dtype,m);return u.forEach(h=>t.disposeIntermediateTensorInfo(h)),d}var YT={kernelName:ls,backendName:"cpu",kernelFunc:pl};function Nk(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,filter:s}=e,{strides:a,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=n;te([o,s],"conv2d");let p=S.convertConv2DDataFormat(l),m=S.computeConv2DInfo(o.shape,s.shape,a,u,i,c,!1,p),f=m.filterHeight,d=m.filterWidth,h=m.dilationHeight,g=m.dilationWidth,x=m.padInfo.left,w=m.padInfo.top,b=m.dataFormat==="channelsLast",k=new lt(m.outShape,o.dtype),_=y.computeStrides(o.shape),A=y.computeStrides(s.shape),N=_[0],$=b?_[1]:_[2],F=b?_[2]:1,M=b?1:_[1],V=k.strides[0],W=b?k.strides[1]:k.strides[2],U=b?k.strides[2]:1,H=b?1:k.strides[1],q=t.data.get(o.dataId).values,X=t.data.get(s.dataId).values,ne=k.values;for(let Y=0;Y<m.batchSize;++Y){let re=Y*N,J=Y*V;for(let ie=0;ie<m.outHeight;++ie){let ue=J+ie*W,ae=ie*m.strideHeight-w;for(let fe=0;fe<f;++fe){let de=ae+fe*h;if(de<0||de>=m.inHeight)continue;let xe=fe*A[0],we=re+de*$;for(let 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M=Math.max(0,Math.ceil((k-F)/f)),V=Math.min(m.outHeight,(m.inHeight+k-F)/f);for(let W=0;W<g;++W){let U=Math.max(0,Math.ceil((b-W)/d)),H=Math.min(m.outWidth,(m.inWidth+b-W)/d);for(let q=0;q<m.inChannels;++q)for(let X=0;X<m.outChannels;++X){let ne=0;for(let Y=0;Y<m.batchSize;++Y)for(let re=M;re<V;++re){let J=F+re*f-k;for(let ie=U;ie<H;++ie){let ue=W+ie*d-b;x?ne+=N.get(Y,J,ue,q)*$.get(Y,re,ie,X):ne+=N.get(Y,q,J,ue)*$.get(Y,X,re,ie)}}w.set(ne,F,W,q,X)}}}return t.makeTensorInfo(w.shape,w.dtype,w.values)}var JT={kernelName:Wl,backendName:"cpu",kernelFunc:Oq};function Pq(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,filter:s}=e,{inputShape:a,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=n;te([o,s],"conv2dBackpropInput");let p=y.computeStrides(s.shape),m=y.computeStrides(o.shape),f=S.convertConv2DDataFormat(u),d=S.computeConv2DInfo(a,s.shape,i,1,l,c,!1,f),h=new 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QT={kernelName:Jn,backendName:"cpu",kernelFunc:Pq};function Mq(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,filter:s}=e,{strides:a,pad:i,dilations:l}=n;te([o,s],"conv3d");let u=S.computeConv3DInfo(o.shape,s.shape,a,l,i),{filterDepth:c,filterHeight:p,filterWidth:m,dilationDepth:f,dilationHeight:d,dilationWidth:h,padInfo:g}=u,x=g.front,w=g.left,b=g.top,k=new lt(u.outShape,o.dtype),_=t.data.get(o.dataId).values,A=t.data.get(s.dataId).values,N=k.values,$=y.computeStrides(o.shape),F=y.computeStrides(s.shape);for(let M=0;M<u.batchSize;++M){let V=M*$[0],W=M*k.strides[0];for(let U=0;U<u.outDepth;++U){let H=W+U*k.strides[1],q=U*u.strideDepth-x;for(let X=0;X<c;++X){let ne=q+X*f;if(ne<0||ne>=u.inDepth)continue;let Y=X*F[0],re=V+ne*$[1];for(let J=0;J<u.outHeight;++J){let ie=H+J*k.strides[2],ue=J*u.strideHeight-b;for(let ae=0;ae<p;++ae){let fe=ue+ae*d;if(fe<0||fe>=u.inHeight)continue;let de=Y+ae*F[1],xe=re+fe*$[2];for(let we=0;we<u.outWidth;++we){let 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ue=Math.max(0,Math.ceil((Y-ie)/m)),ae=Math.min(p.outDepth,(p.inDepth+Y-ie)/m),fe=ie*k;for(let de=0;de<g;++de){let xe=Math.max(0,Math.ceil((J-de)/f)),we=Math.min(p.outHeight,(p.inHeight+J-de)/f),De=de*_+fe;for(let Ne=0;Ne<x;++Ne){let ze=Math.max(0,Math.ceil((re-Ne)/d)),qe=Math.min(p.outWidth,(p.inWidth+re-Ne)/d),it=Ne*A+De;for(let At=0;At<p.inChannels;++At){let Et=At*N+it;for(let je=0;je<p.outChannels;++je){let ut=0;for(let mt=0;mt<p.batchSize;++mt){let Mt=mt*H,xn=mt*F;for(let Xt=ue;Xt<ae;++Xt){let $r=(ie+Xt*m-Y)*q+Mt,jn=Xt*M+xn;for(let nr=xe;nr<we;++nr){let Gr=(de+nr*f-J)*X+$r,br=nr*V+jn;for(let rn=ze;rn<qe;++rn){let Dl=(Ne+rn*d-re)*ne+Gr,Ua=rn*W+br;ut+=U[Dl+At]*$[Ua+je]}}}}b[Et+je]=ut}}}}}return t.makeTensorInfo(w.shape,w.dtype,w.values)}var t1={kernelName:jl,backendName:"cpu",kernelFunc:Lq};function zq(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,filter:s}=e,{pad:a,strides:i,inputShape:l}=n;te([o],"conv3dBackpropInputV2");let u=y.computeStrides(o.shape),c=y.computeStrides(s.shape),p=S.computeConv3DInfo(l,s.shape,i,1,a),m=new lt(p.inShape,"float32"),f=m.values,[d,h,g,x]=m.strides,w=t.data.get(o.dataId).values,[b,k,_,A]=u,N=t.data.get(s.dataId).values,[$,F,M,V]=c,{batchSize:W,filterDepth:U,filterHeight:H,filterWidth:q,inChannels:X,inDepth:ne,inHeight:Y,inWidth:re,outChannels:J,outDepth:ie,outHeight:ue,outWidth:ae,strideDepth:fe,strideHeight:de,strideWidth:xe}=p,we=U-1-p.padInfo.front,De=H-1-p.padInfo.top,Ne=q-1-p.padInfo.left;for(let ze=0;ze<W;++ze)for(let qe=0;qe<X;++qe)for(let it=0;it<ne;++it){let At=it-we,Et=Math.max(0,Math.ceil(At/fe)),je=Math.min(ie,(U+At)/fe);for(let ut=0;ut<Y;++ut){let mt=ut-De,Mt=Math.max(0,Math.ceil(mt/de)),xn=Math.min(ue,(H+mt)/de);for(let Xt=0;Xt<re;++Xt){let tn=Xt-Ne,$r=Math.max(0,Math.ceil(tn/xe)),jn=Math.min(ae,(q+tn)/xe),nr=0;for(let yn=Et;yn<je;++yn){let Gr=yn*fe-At;for(let br=Mt;br<xn;++br){let rn=br*de-mt;for(let En=$r;En<jn;++En){let 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s1={kernelName:ti,backendName:"cpu",kernelFunc:Gq};function Wq(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{axis:s,exclusive:a,reverse:i}=n;te(o,"cumsum");let l=S.getAxesPermutation([s],o.shape.length),u=o;l!=null&&(u=rr({inputs:{x:o},backend:t,attrs:{perm:l}}));let c=S.getInnerMostAxes(1,o.shape.length)[0];if(c!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${c}`);let p=dr(u.dtype,"int32"),m=y.makeZerosTypedArray(y.sizeFromShape(u.shape),p),f=t.data.get(u.dataId).values,d=u.shape[u.shape.length-1],h=i?(x,w)=>x+d-w-1:(x,w)=>x+w;for(let x=0;x<f.length;x+=d)for(let w=0;w<d;w++){let b=h(x,w);if(w===0)m[b]=a?0:f[b];else{let k=h(x,w-1);m[b]=a?f[k]+m[k]:f[b]+m[k]}}let g=t.makeTensorInfo(u.shape,p,m);if(l!=null){let x=S.getUndoAxesPermutation(l),w=rr({inputs:{x:g},backend:t,attrs:{perm:x}});return t.disposeIntermediateTensorInfo(g),t.disposeIntermediateTensorInfo(u),w}return g}var i1={kernelName:eo,backendName:"cpu",kernelFunc:Wq};function jq(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,weights:s}=e,{size:a,binaryOutput:i}=n;if(o.shape.length===1){let l=t.data.get(o.dataId).values,u=t.data.get(s.dataId).values,c=of(l,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(o.shape.length===2){let l=t.bufferSync(o),u=t.bufferSync(s),c=ck(l,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${o.shape.length}.`)}var a1={kernelName:Hl,backendName:"cpu",kernelFunc:jq};function Uq(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{blockSize:s,dataFormat:a}=n;y.assert(a==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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c=N.computePool3DInfo(s.shape,a,i,1,l,u),p=c.strideDepth,m=c.strideHeight,f=c.strideWidth,d=c.filterDepth,h=c.filterHeight,g=c.filterWidth,x=c.dilationDepth,b=c.dilationHeight,w=c.dilationWidth,k=c.effectiveFilterDepth,_=c.effectiveFilterHeight,D=c.effectiveFilterWidth,T=k-1-c.padInfo.front,R=D-1-c.padInfo.left,O=_-1-c.padInfo.top,M=ve(s.shape,"float32"),G=1/(d*h*g),j=t.bufferSync(n);for(let U=0;U<c.batchSize;++U)for(let H=0;H<c.inChannels;++H)for(let q=0;q<c.inDepth;++q)for(let X=0;X<c.inHeight;++X)for(let oe=0;oe<c.inWidth;++oe){let Y=q-T,re=X-O,J=oe-R,ie=0;for(let ue=0;ue<k;ue+=x){let ae=(Y+ue)/p;if(!(ae<0||ae>=c.outDepth||Math.floor(ae)!==ae))for(let fe=0;fe<_;fe+=b){let de=(re+fe)/m;if(!(de<0||de>=c.outHeight||Math.floor(de)!==de))for(let xe=0;xe<D;xe+=w){let we=(J+xe)/f;if(we<0||we>=c.outWidth||Math.floor(we)!==we)continue;ie+=j.get(U,ae,de,we,H)}}}M.set(ie*G,U,q,X,oe,H)}return t.makeTensorInfo(M.shape,M.dtype,M.values)}var FT={kernelName:Bl,backendName:"cpu",kernelFunc:sq};function iq(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s;te([n,s],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=o,c=N.computePool2DInfo(a.shape,i,l,1,u),p=c.strideHeight,m=c.strideWidth,f=c.filterHeight,d=c.filterWidth,h=c.dilationHeight,g=c.dilationWidth,x=c.effectiveFilterHeight,b=c.effectiveFilterWidth,w=b-1-c.padInfo.left,k=x-1-c.padInfo.top,_=ve(a.shape,"float32"),D=1/(f*d),T=t.data.get(n.dataId).values,R=ve(n.shape,"float32",T);for(let O=0;O<c.batchSize;++O)for(let M=0;M<c.inChannels;++M)for(let G=0;G<c.inHeight;++G)for(let j=0;j<c.inWidth;++j){let U=G-k,H=j-w,q=0;for(let X=0;X<x;X+=h){let oe=(U+X)/p;if(!(oe<0||oe>=c.outHeight||Math.floor(oe)!==oe))for(let Y=0;Y<b;Y+=g){let re=(H+Y)/m;if(re<0||re>=c.outWidth||Math.floor(re)!==re)continue;q+=R.get(O,oe,re,M)}}_.set(q*D,O,G,j,M)}return t.makeTensorInfo(_.shape,_.dtype,_.values)}var OT={kernelName:zl,backendName:"cpu",kernelFunc:iq};function 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t.makeTensorInfo(n.shape,n.dtype,h)}var PT={kernelName:an,backendName:"cpu",kernelFunc:aq};function lq(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,crops:a}=o;te([n],"batchToSpaceND");let i=s.reduce((x,b)=>x*b),l=N.getReshaped(n.shape,s,i),u=N.getPermuted(l.length,s.length),c=N.getReshapedPermuted(n.shape,s,i),p=N.getSliceBeginCoords(a,s.length),m=N.getSliceSize(c,a,s.length),f=Qe({inputs:{x:n},backend:t,attrs:{shape:l}}),d=rr({inputs:{x:f},backend:t,attrs:{perm:u}}),h=Qe({inputs:{x:d},backend:t,attrs:{shape:c}}),g=Kn({inputs:{x:h},backend:t,attrs:{begin:p,size:m}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(h),g}var MT={kernelName:ra,backendName:"cpu",kernelFunc:lq};function uq(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a}=o,i=t.data.get(n.dataId).values,l=t.data.get(s.dataId).values,u=of(i,l,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,u)}var LT={kernelName:Vl,backendName:"cpu",kernelFunc:uq};var cq=$e(Ro,(r,e)=>{let t=e;return r>t.clipValueMax?t.clipValueMax:r<t.clipValueMin?t.clipValueMin:r}),zT={kernelName:Ro,backendName:"cpu",kernelFunc:cq};var pq=r=>{let{x:e}=r.inputs,t=r.backend,o=new Float32Array(y.sizeFromShape(e.shape)),n=t.data.get(e.dataId),s=n.complexTensorInfos.real,a=n.complexTensorInfos.imag,i=t.data.get(s.dataId).values,l=t.data.get(a.dataId).values;for(let u=0;u<i.length;u++){let c=i[u],p=l[u];o[u]=Math.hypot(c,p)}return t.makeOutput(o,e.shape,"float32")},BT={kernelName:oa,backendName:"cpu",kernelFunc:pq};function zi(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.data.get(o.dataId).complexTensorInfos.imag,s=t.data.get(n.dataId).values;return t.makeTensorInfo(n.shape,n.dtype,s)}var VT={kernelName:Ql,backendName:"cpu",kernelFunc:zi};function pl(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o,s=y.parseAxisParam(n,e[0].shape)[0],a=N.computeOutShape(e.map(h=>h.shape),s);if(y.sizeFromShape(a)===0)return 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u.forEach(h=>t.disposeIntermediateTensorInfo(h)),d}var GT={kernelName:ls,backendName:"cpu",kernelFunc:pl};function Ik(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=o;te([n,s],"conv2d");let p=N.convertConv2DDataFormat(l),m=N.computeConv2DInfo(n.shape,s.shape,a,u,i,c,!1,p),f=m.filterHeight,d=m.filterWidth,h=m.dilationHeight,g=m.dilationWidth,x=m.padInfo.left,b=m.padInfo.top,w=m.dataFormat==="channelsLast",k=new lt(m.outShape,n.dtype),_=y.computeStrides(n.shape),D=y.computeStrides(s.shape),T=_[0],R=w?_[1]:_[2],O=w?_[2]:1,M=w?1:_[1],G=k.strides[0],j=w?k.strides[1]:k.strides[2],U=w?k.strides[2]:1,H=w?1:k.strides[1],q=t.data.get(n.dataId).values,X=t.data.get(s.dataId).values,oe=k.values;for(let Y=0;Y<m.batchSize;++Y){let re=Y*T,J=Y*G;for(let ie=0;ie<m.outHeight;++ie){let ue=J+ie*j,ae=ie*m.strideHeight-b;for(let fe=0;fe<f;++fe){let de=ae+fe*h;if(de<0||de>=m.inHeight)continue;let xe=fe*D[0],we=re+de*R;for(let 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JT={kernelName:en,backendName:"cpu",kernelFunc:wq};function kq(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a,binaryOutput:i}=o;if(n.shape.length===1){let l=t.data.get(n.dataId).values,u=t.data.get(s.dataId).values,c=of(l,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(n.shape.length===2){let l=t.bufferSync(n),u=t.bufferSync(s),c=uk(l,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${n.shape.length}.`)}var QT={kernelName:Hl,backendName:"cpu",kernelFunc:kq};function _q(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockSize:s,dataFormat:a}=o;y.assert(a==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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r1={kernelName:ql,backendName:"cpu",kernelFunc:vq};function Cq(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=o;te([n,s],"depthwiseConv2DNativeBackpropInput");let p=y.computeStrides(n.shape),m=y.computeStrides(s.shape),f=N.computeConv2DInfo(c,s.shape,a,i,l,u,!0),d=new lt(f.inShape,"float32"),h=d.values,[g,x,b]=d.strides,w=t.data.get(n.dataId).values,[k,_,D]=p,T=t.data.get(s.dataId).values,[R,O,M]=m,{batchSize:G,filterHeight:j,filterWidth:U,inChannels:H,inHeight:q,inWidth:X,outChannels:oe,outHeight:Y,outWidth:re,strideHeight:J,strideWidth:ie}=f,ue=j-1-f.padInfo.top,ae=U-1-f.padInfo.left,fe=oe/H;for(let de=0;de<G;++de)for(let xe=0;xe<H;++xe)for(let we=0;we<q;++we){let De=we-ue,Ne=Math.max(0,Math.ceil(De/J)),ze=Math.min(Y,(j+De)/J);for(let qe=0;qe<X;++qe){let it=qe-ae,Tt=Math.max(0,Math.ceil(it/ie)),At=Math.min(re,(U+it)/ie),je=0;for(let ut=Ne;ut<ze;++ut){let mt=ut*J-De;for(let Pt=Tt;Pt<At;++Pt){let 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d1={kernelName:ai,backendName:"cpu",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{image:o}=r,n=t,s=y.getTypedArrayFromDType(o.dtype,y.sizeFromShape(o.shape)),[a,i,l,u]=o.shape,c=n.data.get(o.dataId).values;for(let m=0;m<a;m++){let f=m*l*i*u;for(let d=0;d<i;d++){let h=d*(l*u);for(let g=0;g<l;g++){let x=g*u;for(let b=0;b<u;b++){let k=[a,d,g,b][2],_=Math.round(l-k),D=f+h+x+b,T=c[D];if(_>=0&&_<l){let R=_*u,O=f+h+R+b;T=c[O]}s[D]=T}}}}return{dataId:n.write(s,o.shape,o.dtype),shape:o.shape,dtype:o.dtype}}};var Vq=Xe((r,e)=>Math.floor(r/e)),Gq=et(sn,Vq,null,"int32"),h1={kernelName:sn,backendName:"cpu",kernelFunc:Gq};function Wq(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:m,activation:f,leakyreluAlpha:d}=o,h=Ik({inputs:{x:n,filter:s},backend:t,attrs:{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:m}});if(a){let 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H1=Ac(Hw());function Ek(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{dim:s}=o,a=n.shape.length,i=s;if(i===-1&&(i=a-1),i!==a-1)throw Error(`Softmax along a non-last dimension is not yet supported. 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l=i?n:Ek({inputs:{logits:n},backend:t,attrs:{dim:-1}}),u=l.shape[0],c=l.shape[1],p=t.data.get(l.dataId).values,m=[u,s],f=y.makeZerosTypedArray(y.sizeFromShape(m),"int32");for(let d=0;d<u;++d){let h=d*c,g=new Float32Array(c-1);g[0]=p[h];for(let w=1;w<g.length;++w)g[w]=g[w-1]+p[h+w];let x=H1.alea(a.toString()),b=d*s;for(let w=0;w<s;++w){let k=x();f[b+w]=g.length;for(let _=0;_<g.length;_++)if(k<g[_]){f[b+w]=_;break}}}return i||t.disposeIntermediateTensorInfo(l),t.makeTensorInfo(m,"int32",f)}var q1={kernelName:su,backendName:"cpu",kernelFunc:bK};var wK=Ar.nonMaxSuppressionV3Impl;function kK(r){let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l}=o;te(n,"NonMaxSuppression");let u=t.data.get(n.dataId).values,c=t.data.get(s.dataId).values,{selectedIndices:p}=wK(u,c,a,i,l);return t.makeTensorInfo([p.length],"int32",new Int32Array(p))}var K1={kernelName:bi,backendName:"cpu",kernelFunc:kK};var _K=Ar.nonMaxSuppressionV4Impl;function 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WebGLTexture.")}function Gk(r,e){let t=W().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(r<=0||e<=0){let o=`[${r}x${e}]`;throw new Error("Requested texture size "+o+" is invalid.")}if(r>t||e>t){let o=`[${r}x${e}]`,n=`[${t}x${t}]`;throw new Error("Requested texture size "+o+" greater than WebGL maximum on this browser / GPU "+n+".")}}function Wk(r){return Fa(r,()=>r.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function Cg(r,e,t,o,n,s,a){let i=r.getAttribLocation(e,t);return i===-1?!1:(Ie(r,()=>r.bindBuffer(r.ARRAY_BUFFER,o)),Ie(r,()=>r.vertexAttribPointer(i,n,r.FLOAT,!1,s,a)),Ie(r,()=>r.enableVertexAttribArray(i)),!0)}function GA(r,e,t){VA(r,t),Ie(r,()=>r.activeTexture(r.TEXTURE0+t)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,e))}function C6(r,e){VA(r,e),Ie(r,()=>r.activeTexture(r.TEXTURE0+e)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function jk(r,e,t){return Fa(r,()=>r.getUniformLocation(e,t),'uniform "'+t+'" not present in program.')}function Uk(r,e,t){return r.getUniformLocation(e,t)}function Hk(r,e,t,o){Ie(r,()=>GA(r,e,o)),Ie(r,()=>r.uniform1i(t,o))}function I6(r){Ie(r,()=>r.bindFramebuffer(r.FRAMEBUFFER,null)),Ie(r,()=>r.viewport(0,0,r.canvas.width,r.canvas.height)),Ie(r,()=>r.scissor(0,0,r.canvas.width,r.canvas.height))}function yf(r,e,t){Ie(r,()=>r.bindFramebuffer(r.FRAMEBUFFER,t)),Ie(r,()=>r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,e,0))}function Ig(r,e){Ie(r,()=>r.bindFramebuffer(r.FRAMEBUFFER,e)),Ie(r,()=>r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,null,0))}function dp(r){let e=r.checkFramebufferStatus(r.FRAMEBUFFER);if(e!==r.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+WA(r,e))}function WA(r,e){switch(e){case r.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case r.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case r.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case r.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${e}`}}function Fa(r,e,t){let o=Ie(r,()=>e());if(o==null)throw new Error(t);return o}function VA(r,e){let t=r.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,o=e+r.TEXTURE0;if(o<r.TEXTURE0||o>t){let n=`[gl.TEXTURE0, gl.TEXTURE${t}]`;throw new Error(`textureUnit must be in ${n}.`)}}function Oa(r,e=2){return y.sizeFromShape(r.slice(0,r.length-e))}function Pa(r){if(r.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[r.length>1?r[r.length-2]:1,r[r.length-1]]}function bf(r){let e=[1,1,1];return r.length===0||r.length===1&&r[0]===1||(e=[Oa(r),...Pa(r)]),e}function qk(r,e=!1){let t=W().getNumber("WEBGL_MAX_TEXTURE_SIZE");e&&(t=t*2,r=r.map((n,s)=>s>=r.length-2?y.nearestLargerEven(r[s]):r[s]),r.length===1&&(r=[2,r[0]])),r.length!==2&&(r=y.squeezeShape(r).newShape);let o=y.sizeFromShape(r);if(r.length<=1&&o<=t)return[1,o];if(r.length===2&&r[0]<=t&&r[1]<=t)return r;if(r.length===3&&r[0]*r[1]<=t&&r[2]<=t)return[r[0]*r[1],r[2]];if(r.length===3&&r[0]<=t&&r[1]*r[2]<=t)return[r[0],r[1]*r[2]];if(r.length===4&&r[0]*r[1]*r[2]<=t&&r[3]<=t)return[r[0]*r[1]*r[2],r[3]];if(r.length===4&&r[0]<=t&&r[1]*r[2]*r[3]<=t)return[r[0],r[1]*r[2]*r[3]];if(e){let n=Oa(r),s=2,a=2;return r.length&&([s,a]=Pa(r)),o=n*(s/2)*(a/2),y.sizeToSquarishShape(o).map(i=>i*2)}return y.sizeToSquarishShape(o)}function Ng(r){return r%2==0}function dl(r,e){if(r=r.slice(-2),e=e.slice(-2),y.arraysEqual(r,e)||!r.length||!e.length||r[0]===0||r[1]===0||e[0]===0||e[1]===0)return!0;if(r.length!==e.length){let t=r.slice(-1)[0],o=e.slice(-1)[0];if(t===o||Ng(t)&&Ng(o)&&(r[0]===1||e[0]===1))return!0}return r[1]===e[1]&&Ng(r[0])&&Ng(e[0])}var Sg,Tg;function Kk(r){if(Sg==null){let e=Vo(r);Sg=e.getParameter(e.MAX_TEXTURE_SIZE)}return Sg}function N6(){Sg=null}function S6(){Tg=null}function Xk(r){if(Tg==null){let e=Vo(r);Tg=e.getParameter(e.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,Tg)}function Yk(r){if(r===0)return 0;let e,t=Vo(r);return Io(t,"EXT_disjoint_timer_query_webgl2")&&r===2?e=2:Io(t,"EXT_disjoint_timer_query")?e=1:e=0,e}function Io(r,e){return r.getExtension(e)!=null}function Ag(r){try{if(Vo(r)!=null)return!0}catch(e){return console.log("Error when getting WebGL context: ",e),!1}return!1}function Jk(r){if(r===0)return!1;let e=Vo(r);if(r===1){if(!Io(e,"OES_texture_float"))return!1}else if(!Io(e,"EXT_color_buffer_float"))return!1;return Zk(e)}function Qk(r){if(r===0)return!1;let e=Vo(r);if(r===1){if(!Io(e,"OES_texture_float")||!Io(e,"WEBGL_color_buffer_float"))return!1}else{if(Io(e,"EXT_color_buffer_float"))return Zk(e);let o="EXT_color_buffer_half_float";if(Io(e,o)){let n=e.getExtension(o);return T6(e,n)}return!1}return Zk(e)}function Zk(r){let e=gf(r),t=r.createTexture();r.bindTexture(r.TEXTURE_2D,t);let o=1,n=1;r.texImage2D(r.TEXTURE_2D,0,e.internalFormatFloat,o,n,0,e.textureFormatFloat,e.textureTypeFloat,null);let s=r.createFramebuffer();r.bindFramebuffer(r.FRAMEBUFFER,s),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,t,0);let a=r.checkFramebufferStatus(r.FRAMEBUFFER)===r.FRAMEBUFFER_COMPLETE;return r.bindTexture(r.TEXTURE_2D,null),r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteTexture(t),r.deleteFramebuffer(s),a}function T6(r,e){let t=gf(r,e),o=r.createTexture();r.bindTexture(r.TEXTURE_2D,o);let n=1,s=1;r.texImage2D(r.TEXTURE_2D,0,t.internalFormatHalfFloat,n,s,0,t.textureFormatFloat,t.textureTypeHalfFloat,null);let a=r.createFramebuffer();r.bindFramebuffer(r.FRAMEBUFFER,a),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,o,0);let i=r.checkFramebufferStatus(r.FRAMEBUFFER)===r.FRAMEBUFFER_COMPLETE;return r.bindTexture(r.TEXTURE_2D,null),r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteTexture(o),r.deleteFramebuffer(a),i}function e_(r){return r!==2?!1:Vo(r).fenceSync!=null}function Rs(r,e){Array.isArray(r)||(r=[r]),r.forEach(t=>{t!=null&&y.assert(t.dtype!=="complex64",()=>`${e} does not support complex64 tensors in the WebGL backend.`)})}var Pe=W();Pe.registerFlag("HAS_WEBGL",()=>Pe.getNumber("WEBGL_VERSION")>0);Pe.registerFlag("WEBGL_VERSION",()=>Ag(2)?2:Ag(1)?1:0);Pe.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Pe.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Pe.get("WEBGL_VERSION")===2);Pe.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Pe.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Pe.registerFlag("WEBGL_PACK",()=>Pe.getBool("HAS_WEBGL"));Pe.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_CLIP",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>!1);Pe.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_REDUCE",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_LAZILY_UNPACK",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_CONV_IM2COL",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>Kk(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>Xk(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let r=Pe.getNumber("WEBGL_VERSION");return r===0?0:Yk(r)});Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Pe.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!hu.isMobile());Pe.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>Jk(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Pe.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Pe.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Pe.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>Qk(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_FENCE_API_ENABLED",()=>e_(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Pe.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Pe.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,r=>{if(r<0&&r!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${r}.`)});Pe.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>hu.isMobile()&&Pe.getBool("IS_CHROME")?1:-1,r=>{if(r<0&&r!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${r}.`)});function Rt(){let r,e,t,o,n,s,a,i,l,u;return W().getNumber("WEBGL_VERSION")===2?(r="#version 300 es",e="in",t="out",o="in",n="texture",s="outputColor",a="out vec4 outputColor;",i=`
       bool isnan_custom(float val) {
         return (val > 0.0 || val < 0.0) ? false : val != 0.0;
       }
@@ -49,7 +49,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       ivec4 newRound(vec4 value) {
         return ivec4(floor(value + vec4(0.5)));
       }
-    `):(r="",e="attribute",t="varying",n="varying",o="texture2D",s="gl_FragColor",a="",i=`
+    `):(r="",e="attribute",t="varying",o="varying",n="texture2D",s="gl_FragColor",a="",i=`
       #define isnan(value) isnan_custom(value)
       bool isnan_custom(float val) {
         return (val > 0. || val < 1. || val == 0.) ? false : true;
@@ -74,11 +74,11 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       ivec4 round(vec4 value) {
         return ivec4(floor(value + vec4(0.5)));
       }
-    `),{version:r,attribute:e,varyingVs:t,varyingFs:n,texture2D:o,output:s,defineOutput:a,defineSpecialNaN:i,defineSpecialInf:l,defineRound:u}}function Fs(r,e,t="index"){let n=y.computeStrides(e);return n.map((o,s)=>{let a=`int ${r[s]} = ${t} / ${o}`,i=s===n.length-1?`int ${r[s+1]} = ${t} - ${r[s]} * ${o}`:`index -= ${r[s]} * ${o}`;return`${a}; ${i};`}).join("")}function gp(r){let e=y.computeStrides(r).map(t=>t.toString());return`
+    `),{version:r,attribute:e,varyingVs:t,varyingFs:o,texture2D:n,output:s,defineOutput:a,defineSpecialNaN:i,defineSpecialInf:l,defineRound:u}}function Fs(r,e,t="index"){let o=y.computeStrides(e);return o.map((n,s)=>{let a=`int ${r[s]} = ${t} / ${n}`,i=s===o.length-1?`int ${r[s+1]} = ${t} - ${r[s]} * ${n}`:`index -= ${r[s]} * ${n}`;return`${a}; ${i};`}).join("")}function hp(r){let e=y.computeStrides(r).map(t=>t.toString());return`
   int getFlatIndex(ivec3 coords) {
     return coords.x * ${e[0]} + coords.y * ${e[1]} + coords.z;
   }
-`}var Rg=`
+`}var Eg=`
   const float FLOAT_MAX = 1.70141184e38;
   const float FLOAT_MIN = 1.17549435e-38;
 
@@ -117,7 +117,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
     return c / 255.0;
   }
-`;var l_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=ml.DENSE;let t=fl(e),n=Ft();this.outputShape=e,this.userCode=`
+`;var t_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=ml.DENSE;let t=fl(e),o=Rt();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
         ${Fs(["r","c","d"],e)}
         return ivec3(r, c, d);
@@ -136,9 +136,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
           result[i] = getA(rc.x, rc.y, rc.z);
         }
 
-        ${n.output} = result;
+        ${o.output} = result;
       }
-    `}};var u_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=ml.DENSE;let t=fl(e),n=Ft();this.outputShape=e,this.userCode=`
+    `}};var r_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=ml.DENSE;let t=fl(e),o=Rt();this.outputShape=e,this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
         ${Fs(["r","c","d"],e)}
         return ivec3(r, c, d);
@@ -157,25 +157,25 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
           result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
         }
 
-        ${n.output} = result;
+        ${o.output} = result;
       }
-    `}};var c_=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Dr.DOWNLOAD;let t=Ft();this.outputShape=e,this.userCode=`
-      ${Rg}
+    `}};var o_=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Dr.DOWNLOAD;let t=Rt();this.outputShape=e,this.userCode=`
+      ${Eg}
 
       void main() {
         float x = getAAtOutCoords();
         ${t.output} = encode_float(x);
       }
-    `}};var p_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Dr.DOWNLOAD;let t=Ft();this.outputShape=e,this.userCode=`
-      ${Rg}
+    `}};var n_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Dr.DOWNLOAD;let t=Rt();this.outputShape=e,this.userCode=`
+      ${Eg}
 
       void main() {
         ivec3 coords = getOutputCoords();
         float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
         ${t.output} = encode_float(x);
       }
-    `}};var m_=class{constructor(e,t,n=!1){this.variableNames=["A"];let o=Ft(),[s,a]=t;this.outputShape=e;let i="result";n&&(i="floor(result * 255. + 0.5)"),this.userCode=`
-      ${gp(e)}
+    `}};var s_=class{constructor(e,t,o=!1){this.variableNames=["A"];let n=Rt(),[s,a]=t;this.outputShape=e;let i="result";o&&(i="floor(result * 255. + 0.5)"),this.userCode=`
+      ${hp(e)}
 
       void main() {
         ivec3 coords = getOutputCoords();
@@ -188,7 +188,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
         int r = flatIndex / ${a};
         int c = imod(flatIndex, ${a});
         vec2 uv = (vec2(c, r) + halfCR) / vec2(${a}.0, ${s}.0);
-        vec4 values = ${o.texture2D}(A, uv);
+        vec4 values = ${n.texture2D}(A, uv);
 
         float result;
 
@@ -202,9 +202,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
           result = values[3];
         }
 
-        ${o.output} = vec4(${i}, 0., 0., 0.);
+        ${n.output} = vec4(${i}, 0., 0., 0.);
       }
-    `}};var f_=class{constructor(e,t,n=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let o=Ft(),[s,a]=t;this.outputShape=e;let i="",l="result";n&&(l="floor(result * 255. + 0.5)");for(let u=0;u<=1;u++)for(let c=0;c<=1;c++){let p=u*2+c;i+=`
+    `}};var i_=class{constructor(e,t,o=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let n=Rt(),[s,a]=t;this.outputShape=e;let i="",l="result";o&&(l="floor(result * 255. + 0.5)");for(let u=0;u<=1;u++)for(let c=0;c<=1;c++){let p=u*2+c;i+=`
           localCoords = coords;
           if(localCoords[2] + ${c} < ${e[2]}) {
             localCoords[2] += ${c};
@@ -219,7 +219,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
               r = flatIndex / ${a};
               c = imod(flatIndex, ${a});
               uv = (vec2(c, r) + halfCR) / vec2(${a}.0, ${s}.0);
-              values = ${o.texture2D}(A, uv);
+              values = ${n.texture2D}(A, uv);
 
               if(offset == 0) {
                 result[${p}] = values[0];
@@ -233,7 +233,7 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
             }
           }
         `}this.userCode=`
-      ${gp(e)}
+      ${hp(e)}
 
       void main() {
         ivec3 coords = getOutputCoords();
@@ -246,9 +246,9 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
 
         ${i}
 
-        ${o.output} = ${l};
+        ${n.output} = ${l};
       }
-    `}};var fE={};Ke(fE,{bindVertexProgramAttributeStreams:()=>__,createBufferFromOutputTexture:()=>I_,createFloat16MatrixTexture:()=>y_,createFloat16PackedMatrixTexture:()=>k_,createFloat32MatrixTexture:()=>x_,createIndexBuffer:()=>g_,createPackedMatrixTexture:()=>w_,createUnsignedBytesMatrixTexture:()=>b_,createVertexBuffer:()=>h_,createVertexShader:()=>d_,downloadByteEncodedFloatMatrixFromOutputTexture:()=>S_,downloadFloat32MatrixFromBuffer:()=>N_,downloadMatrixFromPackedOutputTexture:()=>A_,downloadPackedMatrixFromBuffer:()=>T_,getInternalFormatForFloat16MatrixTexture:()=>Og,getInternalFormatForFloat16PackedMatrixTexture:()=>Lg,getInternalFormatForFloat32MatrixTexture:()=>Fg,getInternalFormatForPackedMatrixTexture:()=>Mg,getInternalFormatForUnsignedBytesMatrixTexture:()=>Pg,uploadDenseMatrixToTexture:()=>v_,uploadPixelDataToTexture:()=>C_});function d_(r){let e=Ft(),t=`${e.version}
+    `}};var jA={};Ke(jA,{bindVertexProgramAttributeStreams:()=>h_,createBufferFromOutputTexture:()=>y_,createFloat16MatrixTexture:()=>p_,createFloat16PackedMatrixTexture:()=>d_,createFloat32MatrixTexture:()=>c_,createIndexBuffer:()=>u_,createPackedMatrixTexture:()=>f_,createUnsignedBytesMatrixTexture:()=>m_,createVertexBuffer:()=>l_,createVertexShader:()=>a_,downloadByteEncodedFloatMatrixFromOutputTexture:()=>w_,downloadFloat32MatrixFromBuffer:()=>b_,downloadMatrixFromPackedOutputTexture:()=>__,downloadPackedMatrixFromBuffer:()=>k_,getInternalFormatForFloat16MatrixTexture:()=>$g,getInternalFormatForFloat16PackedMatrixTexture:()=>Og,getInternalFormatForFloat32MatrixTexture:()=>Dg,getInternalFormatForPackedMatrixTexture:()=>Fg,getInternalFormatForUnsignedBytesMatrixTexture:()=>Rg,uploadDenseMatrixToTexture:()=>g_,uploadPixelDataToTexture:()=>x_});function a_(r){let e=Rt(),t=`${e.version}
     precision highp float;
     ${e.attribute} vec3 clipSpacePos;
     ${e.attribute} vec2 uv;
@@ -257,22 +257,22 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
     void main() {
       gl_Position = vec4(clipSpacePos, 1);
       resultUV = uv;
-    }`;return Gk(r,t)}function h_(r){let e=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return Hk(r,e)}function g_(r){let e=new Uint16Array([0,1,2,2,1,3]);return qk(r,e)}function kf(r,e,t,n,o,s){Xk(e,t);let a=Kk(r),i=r.TEXTURE_2D;return Ie(r,()=>r.bindTexture(i,a)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_WRAP_S,r.CLAMP_TO_EDGE)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_WRAP_T,r.CLAMP_TO_EDGE)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_MIN_FILTER,r.NEAREST)),Ie(r,()=>r.texParameteri(i,r.TEXTURE_MAG_FILTER,r.NEAREST)),Ie(r,()=>r.texImage2D(i,0,n,e,t,0,o,s,null)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null)),a}function Fg(r){return r.internalFormatFloat}function x_(r,e,t,n){let[o,s]=Yu(e,t);return kf(r,o,s,Fg(n),n.textureFormatFloat,r.FLOAT)}function Og(r){return r.internalFormatHalfFloat}function y_(r,e,t,n){let[o,s]=Yu(e,t);return kf(r,o,s,Og(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function Pg(r){return r.downloadTextureFormat}function b_(r,e,t,n){let[o,s]=Yu(e,t);return kf(r,o,s,Pg(n),r.RGBA,r.UNSIGNED_BYTE)}function Mg(r){return r.internalFormatPackedFloat}function w_(r,e,t,n){let[o,s]=Bi(e,t);return kf(r,o,s,Mg(n),r.RGBA,r.FLOAT)}function Lg(r){return r.internalFormatPackedHalfFloat}function k_(r,e,t,n){let[o,s]=Bi(e,t);return kf(r,o,s,Lg(n),r.RGBA,n.textureTypeHalfFloat)}function __(r,e,t){let n=0,o=3*4,s=3*4+2*4;return Ie(r,()=>r.bindBuffer(r.ARRAY_BUFFER,t)),Sg(r,e,"clipSpacePos",t,3,s,n)&&Sg(r,e,"uv",t,2,s,o)}function v_(r,e,t,n,o,s){Ie(r,()=>r.bindTexture(r.TEXTURE_2D,e));let a,i,l;o instanceof Uint8Array?(a=new Uint8Array(t*n*4),i=r.UNSIGNED_BYTE,l=r.RGBA):(a=new Float32Array(t*n*4),i=r.FLOAT,l=s.internalFormatPackedFloat),a.set(o),Ie(r,()=>r.texImage2D(r.TEXTURE_2D,0,l,t,n,0,r.RGBA,i,a)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function C_(r,e,t){Ie(r,()=>r.bindTexture(r.TEXTURE_2D,e)),t.data instanceof Uint8Array?Ie(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,t.width,t.height,0,r.RGBA,r.UNSIGNED_BYTE,t.data)):Ie(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,r.RGBA,r.UNSIGNED_BYTE,t)),Ie(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function I_(r,e,t,n){let o=r.createBuffer();Ie(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,o));let i=4*4*e*t;return Ie(r,()=>r.bufferData(r.PIXEL_PACK_BUFFER,i,r.STREAM_READ)),Ie(r,()=>r.readPixels(0,0,t,e,r.RGBA,r.FLOAT,0)),Ie(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,null)),o}function N_(r,e,t){let n=r,o=new Float32Array(t);return n.bindBuffer(n.PIXEL_PACK_BUFFER,e),n.getBufferSubData(n.PIXEL_PACK_BUFFER,0,o),n.bindBuffer(n.PIXEL_PACK_BUFFER,null),o}function S_(r,e,t,n){let[o,s]=Yu(e,t),a=4,i=new Uint8Array(iE(e*t,a));return Ie(r,()=>r.readPixels(0,0,o,s,n.downloadTextureFormat,r.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function T_(r,e,t,n,o,s,a,i){let l=r,u=new Float32Array(aE(s,a));return l.bindBuffer(l.PIXEL_PACK_BUFFER,e),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function A_(r,e,t){let n=new Float32Array(e*t*4);return Ie(r,()=>r.readPixels(0,0,t,e,r.RGBA,r.FLOAT,n)),n}var zg=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=j().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,Bk(t,e)):this.gl=Vn(t);let n="WEBGL_color_buffer_float",o="EXT_color_buffer_half_float";if(j().getNumber("WEBGL_VERSION")===1){let s="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=dp(this.gl,s),In(this.gl,a))this.textureHalfFloatExtension=dp(this.gl,a);else if(j().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),In(this.gl,o))this.colorBufferHalfFloatExtension=dp(this.gl,o);else if(j().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",In(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(In(this.gl,o))this.colorBufferHalfFloatExtension=this.gl.getExtension(o);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=h_(this.gl),this.indexBuffer=g_(this.gl),this.framebuffer=Yk(this.gl),this.textureConfig=xf(this.gl,this.textureHalfFloatExtension)}get debug(){return j().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. 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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(),c_(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),p_(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),m_(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),x_(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,o,n){this.throwIfDisposed(),g_(this.gl,e,t,o,n,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),d_(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),f_(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(Ig(this.gl,this.framebuffer),this.outputTexture=null),Ie(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,o){return this.downloadMatrixDriver(e,()=>w_(this.gl,t,o,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,o,n,s,a){return k_(this.gl,e,t,o,n,s,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return b_(this.gl,e,t)}createBufferFromTexture(e,t,o){this.bindTextureToFrameBuffer(e);let n=y_(this.gl,t,o,this.textureConfig);return this.unbindTextureToFrameBuffer(),n}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,o;if(W().getBool("WEBGL_FENCE_API_ENABLED")){let n=e,s=n.fenceSync(n.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),o=()=>{let a=n.clientWaitSync(s,0,0);return a===n.ALREADY_SIGNALED||a===n.CONDITION_SATISFIED},t=s}else W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),o=()=>this.isQueryAvailable(t,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):o=()=>!0;return{query:t,isFencePassed:o}}downloadMatrixFromPackedTexture(e,t,o){return this.downloadMatrixDriver(e,()=>__(this.gl,t,o))}createProgram(e){this.throwIfDisposed();let t=this.gl,o=Pk(t,e),n=a_(t),s=Mk(t);return Ie(t,()=>t.attachShader(s,n)),Ie(t,()=>t.attachShader(s,o)),Lk(t,s),this.debug&&xf(t,s),this.vertexAttrsAreBound||(this.setProgram(s),this.vertexAttrsAreBound=h_(t,this.program,this.vertexBuffer)),s}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&&xf(this.gl,this.program),Ie(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,o=!0){return this.throwIfDisposed(),o?jk(this.gl,e,t):Uk(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,o){this.throwIfDisposed(),this.throwIfNoProgram(),Hk(this.gl,e,t,o)}setOutputMatrixTexture(e,t,o){this.setOutputMatrixTextureDriver(e,o,t)}setOutputPackedMatrixTexture(e,t,o){this.throwIfDisposed();let[n,s]=Bi(t,o);this.setOutputMatrixTextureDriver(e,n,s)}setOutputMatrixWriteRegion(e,t,o,n){this.setOutputMatrixWriteRegionDriver(o,e,n,t)}setOutputPackedMatrixWriteRegion(e,t,o,n){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&xf(this.gl,this.program),dp(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),Ie(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=fp(this.gl,W().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(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let o=this.gl,n=this.getQueryTimerExtensionWebGL2(),s=o.createQuery();return o.beginQuery(n.TIME_ELAPSED_EXT,s),s}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,o=this.getQueryTimerExtensionWebGL2();t.endQuery(o.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await y.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let o=this.gl;return o.getQueryParameter(e,o.QUERY_RESULT)/1e6}else{let o=this.getQueryTimerExtensionWebGL1();return o.getQueryObjectEXT(e,o.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let o=this.gl,n=this.getQueryTimerExtensionWebGL2(),s=o.getQueryParameter(e,o.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),s&&!this.disjoint}else{let o=this.getQueryTimerExtensionWebGL1(),n=o.getQueryObjectEXT(e,o.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(o.GPU_DISJOINT_EXT)),n&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=A6(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:o}=this.itemsToPoll[t];o()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&y.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),yf(this.gl,e,this.framebuffer),this.debug&&dp(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(yf(this.gl,this.outputTexture,this.framebuffer),this.debug&&dp(this.gl)):Ig(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let o=t();return this.unbindTextureToFrameBuffer(),o}setOutputMatrixTextureDriver(e,t,o){this.throwIfDisposed();let n=this.gl;yf(n,e,this.framebuffer),this.debug&&dp(n),this.outputTexture=e,Ie(n,()=>n.viewport(0,0,t,o)),Ie(n,()=>n.scissor(0,0,t,o))}setOutputMatrixWriteRegionDriver(e,t,o,n){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.scissor(e,t,o,n))}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 A6(r){let e=0;for(;e<r.length&&r[e]();++e);return e-1}var{getBroadcastDims:UA}=N;function HA(r,e,t,o){let n=[];r.forEach(d=>{let h=y.sizeFromShape(d.shapeInfo.logicalShape);d.shapeInfo.isUniform?n.push(`uniform float ${d.name}${h>1?`[${h}]`:""};`):(n.push(`uniform sampler2D ${d.name};`),n.push(`uniform int offset${d.name};`))});let s=n.join(`
+`),a=r.map(d=>E6(d,e,o)).join(`
+`),i=e.texShape,l=Rt(),u=R6(l),c,p,m=P6(l);return e.isPacked?(c=D6(e.logicalShape,i),p=O6(l)):(c=$6(e.logicalShape,i),p=F6(l)),o&&(m+=M6),[m,u,p,s,c,a,t].join(`
+`)}function gp(r){let e=r.shapeInfo.logicalShape;switch(e.length){case 0:return L6(r);case 1:return z6(r);case 2:return B6(r);case 3:return V6(r);case 4:return G6(r);case 5:return W6(r);case 6:return j6(r);default:throw new Error(`${e.length}-D input sampling is not yet supported`)}}function qA(r){switch(r.shapeInfo.logicalShape.length){case 0:return U6(r);case 1:return H6(r);case 2:return q6(r);case 3:return K6(r);default:return X6(r)}}function E6(r,e,t=!1){let o="";t?o+=qA(r):o+=gp(r);let n=r.shapeInfo.logicalShape,s=e.logicalShape;return n.length<=s.length&&(t?o+=Y6(r,e):o+=Z6(r,e)),o}function D6(r,e){switch(r.length){case 0:return KA();case 1:return J6(r,e);case 2:return t5(r,e);case 3:return Q6(r,e);default:return e5(r,e)}}function $6(r,e){switch(r.length){case 0:return KA();case 1:return r5(r,e);case 2:return a5(r,e);case 3:return o5(r,e);case 4:return n5(r,e);case 5:return s5(r,e);case 6:return i5(r,e);default:throw new Error(`${r.length}-D output sampling is not yet supported`)}}function R6(r){return`
     float sampleTexture(sampler2D textureSampler, vec2 uv) {
       return ${r.texture2D}(textureSampler, uv).r;
     }
-  `}function u5(r){return`
+  `}function F6(r){return`
     void setOutput(float val) {
       ${r.output} = vec4(val, 0, 0, 0);
     }
-  `}function c5(r){return`
+  `}function O6(r){return`
     void setOutput(vec4 val) {
       ${r.output} = val;
     }
-  `}function p5(r){return`${r.version}
+  `}function P6(r){return`${r.version}
     precision highp float;
     precision highp int;
     precision highp sampler2D;
@@ -327,10 +327,10 @@ Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To spee
       return fract((p3.x + p3.y) * p3.z);
     }
 
-    ${M5}
-    ${L5}
-    ${z5}
-  `}var M5=`
+    ${l5}
+    ${u5}
+    ${c5}
+  `}var l5=`
 vec2 uvFromFlat(int texNumR, int texNumC, int index) {
   int texR = index / texNumC;
   int texC = index - texR * texNumC;
@@ -342,7 +342,7 @@ vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,L5=`
+`,u5=`
 vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texNumC, int row, int col) {
   int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
@@ -350,7 +350,7 @@ vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
   int texC = texelIndex - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,z5=`
+`,c5=`
 vec2 packedUVfrom3D(int texNumR, int texNumC,
     int texelsInBatch, int texelsInLogicalRow, int b,
     int row, int col) {
@@ -359,7 +359,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   int texC = index - texR * texNumC;
   return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
 }
-`,m5=`
+`,M6=`
   float getChannel(vec4 frag, vec2 innerDims) {
     vec2 modCoord = mod(innerDims, 2.);
     return modCoord.x == 0. ?
@@ -370,11 +370,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     float modCoord = mod(float(dim), 2.);
     return modCoord == 0. ? frag.r : frag.g;
   }
-`;function xE(){return`
+`;function KA(){return`
     int getOutputCoords() {
       return 0;
     }
-  `}function S5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];return t[0]===1?`
+  `}function J6(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];return t[0]===1?`
       int getOutputCoords() {
         return 2 * int(resultUV.x * ${t[1]}.0);
       }
@@ -388,7 +388,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${t[0]}, ${t[1]}));
       return 2 * (resTexRC.x * ${t[1]} + resTexRC.y);
     }
-  `}function D5(r,e){return e[0]===1?`
+  `}function r5(r,e){return e[0]===1?`
       int getOutputCoords() {
         return int(resultUV.x * ${e[1]}.0);
       }
@@ -402,21 +402,21 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                              vec2(${e[0]}, ${e[1]}));
       return resTexRC.x * ${e[1]} + resTexRC.y;
     }
-  `}function T5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],n=Math.ceil(r[2]/2),o=n*Math.ceil(r[1]/2);return`
+  `}function Q6(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],o=Math.ceil(r[2]/2),n=o*Math.ceil(r[1]/2);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${t[0]}, ${t[1]}));
       int index = resTexRC.x * ${t[1]} + resTexRC.y;
 
-      int b = index / ${o};
-      index -= b * ${o};
+      int b = index / ${n};
+      index -= b * ${n};
 
-      int r = 2 * (index / ${n});
-      int c = imod(index, ${n}) * 2;
+      int r = 2 * (index / ${o});
+      int c = imod(index, ${o}) * 2;
 
       return ivec3(b, r, c);
     }
-  `}function $5(r,e){let t=Fs(["r","c","d"],r);return`
+  `}function o5(r,e){let t=Fs(["r","c","d"],r);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${e[0]}, ${e[1]}));
@@ -424,7 +424,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${t}
       return ivec3(r, c, d);
     }
-  `}function A5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],n=Math.ceil(r[r.length-1]/2),o=n*Math.ceil(r[r.length-2]/2),s=o,a="",i="b, r, c";for(let l=2;l<r.length-1;l++)s*=r[r.length-l-1],a=`
+  `}function e5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)],o=Math.ceil(r[r.length-1]/2),n=o*Math.ceil(r[r.length-2]/2),s=n,a="",i="b, r, c";for(let l=2;l<r.length-1;l++)s*=r[r.length-l-1],a=`
       int b${l} = index / ${s};
       index -= b${l} * ${s};
     `+a,i=`b${l}, `+i;return`
@@ -435,15 +435,15 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
       ${a}
 
-      int b = index / ${o};
-      index -= b * ${o};
+      int b = index / ${n};
+      index -= b * ${n};
 
-      int r = 2 * (index / ${n});
-      int c = imod(index, ${n}) * 2;
+      int r = 2 * (index / ${o});
+      int c = imod(index, ${o}) * 2;
 
       return ivec${r.length}(${i});
     }
-  `}function R5(r,e){let t=Fs(["r","c","d","d2"],r);return`
+  `}function n5(r,e){let t=Fs(["r","c","d","d2"],r);return`
     ivec4 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${e[0]}, ${e[1]}));
@@ -451,7 +451,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${t}
       return ivec4(r, c, d, d2);
     }
-  `}function F5(r,e){let t=Fs(["r","c","d","d2","d3"],r);return`
+  `}function s5(r,e){let t=Fs(["r","c","d","d2","d3"],r);return`
     ivec5 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx * vec2(${e[0]},
                              ${e[1]}));
@@ -463,7 +463,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec5 outShape = ivec5(r, c, d, d2, d3);
       return outShape;
     }
-  `}function O5(r,e){let t=Fs(["r","c","d","d2","d3","d4"],r);return`
+  `}function i5(r,e){let t=Fs(["r","c","d","d2","d3","d4"],r);return`
     ivec6 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${e[0]}, ${e[1]}));
@@ -474,22 +474,22 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec6 result = ivec6(r, c, d, d2, d3, d4);
       return result;
     }
-  `}function E5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(y.arraysEqual(r,e))return`
+  `}function t5(r,e){let t=[Math.ceil(e[0]/2),Math.ceil(e[1]/2)];if(y.arraysEqual(r,e))return`
       ivec2 getOutputCoords() {
         return 2 * ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
       }
-    `;let n=Math.ceil(r[1]/2);return`
+    `;let o=Math.ceil(r[1]/2);return`
     ivec2 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${t[0]}, ${t[1]}));
 
       int index = resTexRC.x * ${t[1]} + resTexRC.y;
-      int r = 2 * (index / ${n});
-      int c = imod(index, ${n}) * 2;
+      int r = 2 * (index / ${o});
+      int c = imod(index, ${o}) * 2;
 
       return ivec2(r, c);
     }
-  `}function P5(r,e){return y.arraysEqual(r,e)?`
+  `}function a5(r,e){return y.arraysEqual(r,e)?`
       ivec2 getOutputCoords() {
         return ivec2(resultUV.yx * vec2(${e[0]}, ${e[1]}));
       }
@@ -516,117 +516,117 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       int c = index - r * ${r[1]};
       return ivec2(r, c);
     }
-  `}function Zu(r){return`offset${r}`}function w5(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1),n=Ft();return`
+  `}function Yu(r){return`offset${r}`}function U6(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1),o=Rt();return`
     vec4 ${t}() {
-      return ${n.texture2D}(${e}, halfCR);
+      return ${o.texture2D}(${e}, halfCR);
     }
-  `}function f5(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`float ${t}() {return ${e};}`;let[n,o]=r.shapeInfo.texShape;if(n===1&&o===1)return`
+  `}function L6(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`float ${t}() {return ${e};}`;let[o,n]=r.shapeInfo.texShape;if(o===1&&n===1)return`
       float ${t}() {
         return sampleTexture(${e}, halfCR);
       }
-    `;let[s,a]=r.shapeInfo.texShape,i=Zu(e);return`
+    `;let[s,a]=r.shapeInfo.texShape,i=Yu(e);return`
     float ${t}() {
       vec2 uv = uvFromFlat(${s}, ${a}, ${i});
       return sampleTexture(${e}, uv);
     }
-  `}function k5(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1),n=r.shapeInfo.texShape,o=[Math.ceil(n[0]/2),Math.ceil(n[1]/2)],s=Ft();return`
+  `}function H6(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1),o=r.shapeInfo.texShape,n=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],s=Rt();return`
     vec4 ${t}(int index) {
       vec2 uv = packedUVfrom1D(
-        ${o[0]}, ${o[1]}, index);
+        ${n[0]}, ${n[1]}, index);
       return ${s.texture2D}(${e}, uv);
     }
-  `}function d5(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`
+  `}function z6(r){let e=r.name,t="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`
       float ${t}(int index) {
-        ${yp(r)}
+        ${xp(r)}
       }
-    `;let n=r.shapeInfo.texShape,o=n[0],s=n[1];if(s===1&&o===1)return`
+    `;let o=r.shapeInfo.texShape,n=o[0],s=o[1];if(s===1&&n===1)return`
       float ${t}(int index) {
         return sampleTexture(${e}, halfCR);
       }
-    `;let a=Zu(e);return s===1?`
+    `;let a=Yu(e);return s===1?`
       float ${t}(int index) {
-        vec2 uv = vec2(0.5, (float(index + ${a}) + 0.5) / ${o}.0);
+        vec2 uv = vec2(0.5, (float(index + ${a}) + 0.5) / ${n}.0);
         return sampleTexture(${e}, uv);
       }
-    `:o===1?`
+    `:n===1?`
       float ${t}(int index) {
         vec2 uv = vec2((float(index + ${a}) + 0.5) / ${s}.0, 0.5);
         return sampleTexture(${e}, uv);
       }
     `:`
     float ${t}(int index) {
-      vec2 uv = uvFromFlat(${o}, ${s}, index + ${a});
+      vec2 uv = uvFromFlat(${n}, ${s}, index + ${a});
       return sampleTexture(${e}, uv);
     }
-  `}function _5(r){let e=r.shapeInfo.logicalShape,t=r.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),o=r.shapeInfo.texShape,s=o[0],a=o[1],i=Ft();if(o!=null&&y.arraysEqual(e,o))return`
-      vec4 ${n}(int row, int col) {
+  `}function q6(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape,s=n[0],a=n[1],i=Rt();if(n!=null&&y.arraysEqual(e,n))return`
+      vec4 ${o}(int row, int col) {
         vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}.0, ${s}.0);
 
         return ${i.texture2D}(${t}, uv);
       }
-    `;let l=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],u=Math.ceil(e[1]/2);return`
-    vec4 ${n}(int row, int col) {
+    `;let l=[Math.ceil(n[0]/2),Math.ceil(n[1]/2)],u=Math.ceil(e[1]/2);return`
+    vec4 ${o}(int row, int col) {
       vec2 uv = packedUVfrom2D(${u}, ${l[0]}, ${l[1]}, row, col);
       return ${i.texture2D}(${t}, uv);
     }
-  `}function h5(r){let e=r.shapeInfo.logicalShape,t=r.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),o=r.shapeInfo.texShape;if(o!=null&&y.arraysEqual(e,o)){let p=o[0],m=o[1];return`
-    float ${n}(int row, int col) {
+  `}function B6(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape;if(n!=null&&y.arraysEqual(e,n)){let p=n[0],m=n[1];return`
+    float ${o}(int row, int col) {
       vec2 uv = (vec2(col, row) + halfCR) / vec2(${m}.0, ${p}.0);
       return sampleTexture(${t}, uv);
     }
-  `}let{newShape:s,keptDims:a}=y.squeezeShape(e),i=s;if(i.length<e.length){let p=bp(r,i),m=["row","col"];return`
-      ${xp(p)}
-      float ${n}(int row, int col) {
-        return ${n}(${wp(m,a)});
+  `}let{newShape:s,keptDims:a}=y.squeezeShape(e),i=s;if(i.length<e.length){let p=yp(r,i),m=["row","col"];return`
+      ${gp(p)}
+      float ${o}(int row, int col) {
+        return ${o}(${bp(m,a)});
       }
     `}if(r.shapeInfo.isUniform)return`
-      float ${n}(int row, int col) {
+      float ${o}(int row, int col) {
         int index = round(dot(vec2(row, col), vec2(${e[1]}, 1)));
-        ${yp(r)}
+        ${xp(r)}
       }
-    `;let l=o[0],u=o[1],c=Zu(t);return u===1?`
-    float ${n}(int row, int col) {
+    `;let l=n[0],u=n[1],c=Yu(t);return u===1?`
+    float ${o}(int row, int col) {
       float index = dot(vec3(row, col, ${c}), vec3(${e[1]}, 1, 1));
       vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
       return sampleTexture(${t}, uv);
     }
   `:l===1?`
-    float ${n}(int row, int col) {
+    float ${o}(int row, int col) {
       float index = dot(vec3(row, col, ${c}), vec3(${e[1]}, 1, 1));
       vec2 uv = vec2((index + 0.5) / ${u}.0, 0.5);
       return sampleTexture(${t}, uv);
     }
   `:`
-  float ${n}(int row, int col) {
+  float ${o}(int row, int col) {
     // Explicitly use integer operations as dot() only works on floats.
     int index = row * ${e[1]} + col + ${c};
     vec2 uv = uvFromFlat(${l}, ${u}, index);
     return sampleTexture(${t}, uv);
   }
-`}function v5(r){let e=r.shapeInfo.logicalShape,t=r.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),o=r.shapeInfo.texShape,s=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];if(e[0]===1){let p=e.slice(1),m=[1,2],f=bp(r,p),d=["b","row","col"];return`
-        ${gE(f)}
-        vec4 ${n}(int b, int row, int col) {
-          return ${n}(${wp(d,m)});
+`}function K6(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=r.shapeInfo.texShape,s=[Math.ceil(n[0]/2),Math.ceil(n[1]/2)];if(e[0]===1){let p=e.slice(1),m=[1,2],f=yp(r,p),d=["b","row","col"];return`
+        ${qA(f)}
+        vec4 ${o}(int b, int row, int col) {
+          return ${o}(${bp(d,m)});
         }
-      `}let a=s[0],i=s[1],l=Math.ceil(e[2]/2),u=l*Math.ceil(e[1]/2),c=Ft();return`
-    vec4 ${n}(int b, int row, int col) {
+      `}let a=s[0],i=s[1],l=Math.ceil(e[2]/2),u=l*Math.ceil(e[1]/2),c=Rt();return`
+    vec4 ${o}(int b, int row, int col) {
       vec2 uv = packedUVfrom3D(
         ${a}, ${i}, ${u}, ${l}, b, row, col);
       return ${c.texture2D}(${t}, uv);
     }
-  `}function g5(r){let e=r.shapeInfo.logicalShape,t=r.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),o=e[1]*e[2],s=e[2],{newShape:a,keptDims:i}=y.squeezeShape(e),l=a;if(l.length<e.length){let d=bp(r,l),h=["row","col","depth"];return`
-        ${xp(d)}
-        float ${n}(int row, int col, int depth) {
-          return ${n}(${wp(h,i)});
+  `}function V6(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[1]*e[2],s=e[2],{newShape:a,keptDims:i}=y.squeezeShape(e),l=a;if(l.length<e.length){let d=yp(r,l),h=["row","col","depth"];return`
+        ${gp(d)}
+        float ${o}(int row, int col, int depth) {
+          return ${o}(${bp(h,i)});
         }
       `}if(r.shapeInfo.isUniform)return`
-      float ${n}(int row, int col, int depth) {
+      float ${o}(int row, int col, int depth) {
         int index = round(dot(vec3(row, col, depth),
-                          vec3(${o}, ${s}, 1)));
-        ${yp(r)}
+                          vec3(${n}, ${s}, 1)));
+        ${xp(r)}
       }
-    `;let u=r.shapeInfo.texShape,c=u[0],p=u[1],m=r.shapeInfo.flatOffset;if(p===o&&m==null)return`
-        float ${n}(int row, int col, int depth) {
+    `;let u=r.shapeInfo.texShape,c=u[0],p=u[1],m=r.shapeInfo.flatOffset;if(p===n&&m==null)return`
+        float ${o}(int row, int col, int depth) {
           float texR = float(row);
           float texC = dot(vec2(col, depth), vec2(${s}, 1));
           vec2 uv = (vec2(texC, texR) + halfCR) /
@@ -634,50 +634,50 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           return sampleTexture(${t}, uv);
         }
       `;if(p===s&&m==null)return`
-    float ${n}(int row, int col, int depth) {
+    float ${o}(int row, int col, int depth) {
       float texR = dot(vec2(row, col), vec2(${e[1]}, 1));
       float texC = float(depth);
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}.0, ${c}.0);
       return sampleTexture(${t}, uv);
     }
-  `;let f=Zu(t);return`
-      float ${n}(int row, int col, int depth) {
+  `;let f=Yu(t);return`
+      float ${o}(int row, int col, int depth) {
         // Explicitly use integer operations as dot() only works on floats.
-        int index = row * ${o} + col * ${s} + depth + ${f};
+        int index = row * ${n} + col * ${s} + depth + ${f};
         vec2 uv = uvFromFlat(${c}, ${p}, index);
         return sampleTexture(${t}, uv);
       }
-  `}function C5(r){let e=r.shapeInfo.logicalShape,t=e.length,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape,a=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],i=a[0],l=a[1],u=Math.ceil(e[t-1]/2),c=u*Math.ceil(e[t-2]/2),p="int b, int row, int col",m=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let d=2;d<t-1;d++)p=`int b${d}, `+p,c*=e[t-d-1],m=`b${d} * ${c} + `+m;let f=Ft();return`
-    vec4 ${o}(${p}) {
+  `}function X6(r){let e=r.shapeInfo.logicalShape,t=e.length,o=r.name,n="get"+o.charAt(0).toUpperCase()+o.slice(1),s=r.shapeInfo.texShape,a=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],i=a[0],l=a[1],u=Math.ceil(e[t-1]/2),c=u*Math.ceil(e[t-2]/2),p="int b, int row, int col",m=`b * ${c} + (row / 2) * ${u} + (col / 2)`;for(let d=2;d<t-1;d++)p=`int b${d}, `+p,c*=e[t-d-1],m=`b${d} * ${c} + `+m;let f=Rt();return`
+    vec4 ${n}(${p}) {
       int index = ${m};
       int texR = index / ${l};
       int texC = index - texR * ${l};
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${i});
-      return ${f.texture2D}(${n}, uv);
+      return ${f.texture2D}(${o}, uv);
     }
-  `}function x5(r){let e=r.shapeInfo.logicalShape,t=r.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),o=e[3],s=e[2]*o,a=e[1]*s,{newShape:i,keptDims:l}=y.squeezeShape(e);if(i.length<e.length){let d=bp(r,i),h=["row","col","depth","depth2"];return`
-      ${xp(d)}
-      float ${n}(int row, int col, int depth, int depth2) {
-        return ${n}(${wp(h,l)});
+  `}function G6(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[3],s=e[2]*n,a=e[1]*s,{newShape:i,keptDims:l}=y.squeezeShape(e);if(i.length<e.length){let d=yp(r,i),h=["row","col","depth","depth2"];return`
+      ${gp(d)}
+      float ${o}(int row, int col, int depth, int depth2) {
+        return ${o}(${bp(h,l)});
       }
     `}if(r.shapeInfo.isUniform)return`
-      float ${n}(int row, int col, int depth, int depth2) {
+      float ${o}(int row, int col, int depth, int depth2) {
         int index = round(dot(vec4(row, col, depth, depth2),
-                          vec4(${a}, ${s}, ${o}, 1)));
-        ${yp(r)}
+                          vec4(${a}, ${s}, ${n}, 1)));
+        ${xp(r)}
       }
     `;let u=r.shapeInfo.flatOffset,c=r.shapeInfo.texShape,p=c[0],m=c[1];if(m===a&&u==null)return`
-      float ${n}(int row, int col, int depth, int depth2) {
+      float ${o}(int row, int col, int depth, int depth2) {
         float texR = float(row);
         float texC =
             dot(vec3(col, depth, depth2),
-                vec3(${s}, ${o}, 1));
+                vec3(${s}, ${n}, 1));
         vec2 uv = (vec2(texC, texR) + halfCR) /
                    vec2(${m}.0, ${p}.0);
         return sampleTexture(${t}, uv);
       }
-    `;if(m===o&&u==null)return`
-      float ${n}(int row, int col, int depth, int depth2) {
+    `;if(m===n&&u==null)return`
+      float ${o}(int row, int col, int depth, int depth2) {
         float texR = dot(vec3(row, col, depth),
                          vec3(${e[1]*e[2]}, ${e[2]}, 1));
         float texC = float(depth2);
@@ -685,38 +685,38 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${m}.0, ${p}.0);
         return sampleTexture(${t}, uv);
       }
-    `;let f=Zu(t);return`
-    float ${n}(int row, int col, int depth, int depth2) {
+    `;let f=Yu(t);return`
+    float ${o}(int row, int col, int depth, int depth2) {
       // Explicitly use integer operations as dot() only works on floats.
       int index = row * ${a} + col * ${s} +
-          depth * ${o} + depth2;
+          depth * ${n} + depth2;
       vec2 uv = uvFromFlat(${p}, ${m}, index + ${f});
       return sampleTexture(${t}, uv);
     }
-  `}function y5(r){let e=r.shapeInfo.logicalShape,t=r.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),o=e[4],s=e[3]*o,a=e[2]*s,i=e[1]*a,{newShape:l,keptDims:u}=y.squeezeShape(e);if(l.length<e.length){let h=bp(r,l),g=["row","col","depth","depth2","depth3"];return`
-      ${xp(h)}
-      float ${n}(int row, int col, int depth, int depth2, int depth3) {
-        return ${n}(${wp(g,u)});
+  `}function W6(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),n=e[4],s=e[3]*n,a=e[2]*s,i=e[1]*a,{newShape:l,keptDims:u}=y.squeezeShape(e);if(l.length<e.length){let h=yp(r,l),g=["row","col","depth","depth2","depth3"];return`
+      ${gp(h)}
+      float ${o}(int row, int col, int depth, int depth2, int depth3) {
+        return ${o}(${bp(g,u)});
       }
     `}if(r.shapeInfo.isUniform)return`
-      float ${n}(int row, int col, int depth, int depth2, int depth3) {
+      float ${o}(int row, int col, int depth, int depth2, int depth3) {
         float index = dot(
           vec4(row, col, depth, depth2),
-          vec4(${i}, ${a}, ${s}, ${o})) +
+          vec4(${i}, ${a}, ${s}, ${n})) +
           depth3;
-        ${yp(r)}
+        ${xp(r)}
       }
     `;let c=r.shapeInfo.flatOffset,p=r.shapeInfo.texShape,m=p[0],f=p[1];if(f===i&&c==null)return`
-      float ${n}(int row, int col, int depth, int depth2, int depth3) {
+      float ${o}(int row, int col, int depth, int depth2, int depth3) {
         int texR = row;
         float texC = dot(vec4(col, depth, depth2, depth3),
-                         vec4(${a}, ${s}, ${o}, 1));
+                         vec4(${a}, ${s}, ${n}, 1));
         vec2 uv = (vec2(texC, texR) + halfCR) /
                    vec2(${f}.0, ${m}.0);
         return sampleTexture(${t}, uv);
       }
-    `;if(f===o&&c==null)return`
-      float ${n}(int row, int col, int depth, int depth2, int depth3) {
+    `;if(f===n&&c==null)return`
+      float ${o}(int row, int col, int depth, int depth2, int depth3) {
         float texR = dot(
           vec4(row, col, depth, depth2),
           vec4(${e[1]*e[2]*e[3]},
@@ -726,22 +726,22 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${f}.0, ${m}.0);
         return sampleTexture(${t}, uv);
       }
-    `;let d=Zu(t);return`
-    float ${n}(int row, int col, int depth, int depth2, int depth3) {
+    `;let d=Yu(t);return`
+    float ${o}(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 * ${a} + depth * ${s} +
-          depth2 * ${o} + depth3 + ${d};
+          depth2 * ${n} + depth3 + ${d};
       vec2 uv = uvFromFlat(${m}, ${f}, index);
       return sampleTexture(${t}, uv);
     }
-  `}function b5(r){let e=r.shapeInfo.logicalShape,t=r.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),{newShape:o,keptDims:s}=y.squeezeShape(e);if(o.length<e.length){let g=bp(r,o),x=["row","col","depth","depth2","depth3","depth4"];return`
-      ${xp(g)}
-      float ${n}(int row, int col, int depth,
+  `}function j6(r){let e=r.shapeInfo.logicalShape,t=r.name,o="get"+t.charAt(0).toUpperCase()+t.slice(1),{newShape:n,keptDims:s}=y.squeezeShape(e);if(n.length<e.length){let g=yp(r,n),x=["row","col","depth","depth2","depth3","depth4"];return`
+      ${gp(g)}
+      float ${o}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
-        return ${n}(${wp(x,s)});
+        return ${o}(${bp(x,s)});
       }
     `}let a=e[5],i=e[4]*a,l=e[3]*i,u=e[2]*l,c=e[1]*u;if(r.shapeInfo.isUniform)return`
-      float ${n}(int row, int col, int depth,
+      float ${o}(int row, int col, int depth,
                   int depth2, int depth3, int depth4) {
         int index = round(dot(
           vec4(row, col, depth, depth2),
@@ -749,10 +749,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           dot(
             vec2(depth3, depth4),
             vec2(${a}, 1)));
-        ${yp(r)}
+        ${xp(r)}
       }
     `;let p=r.shapeInfo.flatOffset,m=r.shapeInfo.texShape,f=m[0],d=m[1];if(d===c&&p==null)return`
-      float ${n}(int row, int col, int depth,
+      float ${o}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
         int texR = row;
         float texC = dot(vec4(col, depth, depth2, depth3),
@@ -763,7 +763,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         return sampleTexture(${t}, uv);
       }
     `;if(d===a&&p==null)return`
-      float ${n}(int row, int col, int depth,
+      float ${o}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
         float texR = dot(vec4(row, col, depth, depth2),
           vec4(${e[1]*e[2]*e[3]*e[4]},
@@ -775,8 +775,8 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${d}.0, ${f}.0);
         return sampleTexture(${t}, uv);
       }
-    `;let h=Zu(t);return`
-    float ${n}(int row, int col, int depth,
+    `;let h=Yu(t);return`
+    float ${o}(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 * ${l} +
@@ -784,44 +784,44 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${f}, ${d}, index);
       return sampleTexture(${t}, uv);
     }
-  `}function yp(r){let e=r.name,t=y.sizeFromShape(r.shapeInfo.logicalShape);return t<2?`return ${e};`:`
+  `}function xp(r){let e=r.name,t=y.sizeFromShape(r.shapeInfo.logicalShape);return t<2?`return ${e};`:`
     for (int i = 0; i < ${t}; i++) {
       if (i == index) {
         return ${e}[i];
       }
     }
-  `}function I5(r,e){let t=r.name,n=t.charAt(0).toUpperCase()+t.slice(1),o="get"+n+"AtOutCoords",s=r.shapeInfo.logicalShape.length,a=e.logicalShape.length,i=dE(r.shapeInfo.logicalShape,e.logicalShape),l=Le(a),u=a-s,c,p=["x","y","z","w","u","v"];s===0?c="":a<2&&i.length>=1?c="coords = 0;":c=i.map(w=>`coords.${p[w+u]} = 0;`).join(`
-`);let m="";a<2&&s>0?m="coords":m=r.shapeInfo.logicalShape.map((w,b)=>`coords.${p[b+u]}`).join(", ");let f="return outputValue;",h=y.sizeFromShape(r.shapeInfo.logicalShape)===1,x=y.sizeFromShape(e.logicalShape)===1;if(s===1&&!h&&!x)f=`
+  `}function Y6(r,e){let t=r.name,o=t.charAt(0).toUpperCase()+t.slice(1),n="get"+o+"AtOutCoords",s=r.shapeInfo.logicalShape.length,a=e.logicalShape.length,i=UA(r.shapeInfo.logicalShape,e.logicalShape),l=Le(a),u=a-s,c,p=["x","y","z","w","u","v"];s===0?c="":a<2&&i.length>=1?c="coords = 0;":c=i.map(b=>`coords.${p[b+u]} = 0;`).join(`
+`);let m="";a<2&&s>0?m="coords":m=r.shapeInfo.logicalShape.map((b,w)=>`coords.${p[w+u]}`).join(", ");let f="return outputValue;",h=y.sizeFromShape(r.shapeInfo.logicalShape)===1,x=y.sizeFromShape(e.logicalShape)===1;if(s===1&&!h&&!x)f=`
       return vec4(outputValue.xy, outputValue.xy);
     `;else if(h&&!x)a===1?f=`
         return vec4(outputValue.x, outputValue.x, 0., 0.);
       `:f=`
         return vec4(outputValue.x);
-      `;else if(i.length){let w=s-2,b=s-1;i.indexOf(w)>-1&&i.indexOf(b)>-1?f="return vec4(outputValue.x);":i.indexOf(w)>-1?f="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":i.indexOf(b)>-1&&(f="return vec4(outputValue.xx, outputValue.zz);")}return`
-    vec4 ${o}() {
+      `;else if(i.length){let b=s-2,w=s-1;i.indexOf(b)>-1&&i.indexOf(w)>-1?f="return vec4(outputValue.x);":i.indexOf(b)>-1?f="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":i.indexOf(w)>-1&&(f="return vec4(outputValue.xx, outputValue.zz);")}return`
+    vec4 ${n}() {
       ${l} coords = getOutputCoords();
       ${c}
-      vec4 outputValue = get${n}(${m});
+      vec4 outputValue = get${o}(${m});
       ${f}
     }
-  `}function N5(r,e){let t=r.name,n=t.charAt(0).toUpperCase()+t.slice(1),o="get"+n+"AtOutCoords",s=e.texShape,a=r.shapeInfo.texShape,i=r.shapeInfo.logicalShape.length,l=e.logicalShape.length;if(!r.shapeInfo.isUniform&&i===l&&r.shapeInfo.flatOffset==null&&y.arraysEqual(a,s))return`
-      float ${o}() {
+  `}function Z6(r,e){let t=r.name,o=t.charAt(0).toUpperCase()+t.slice(1),n="get"+o+"AtOutCoords",s=e.texShape,a=r.shapeInfo.texShape,i=r.shapeInfo.logicalShape.length,l=e.logicalShape.length;if(!r.shapeInfo.isUniform&&i===l&&r.shapeInfo.flatOffset==null&&y.arraysEqual(a,s))return`
+      float ${n}() {
         return sampleTexture(${t}, resultUV);
       }
-    `;let u=Le(l),c=dE(r.shapeInfo.logicalShape,e.logicalShape),p=l-i,m,f=["x","y","z","w","u","v"];i===0?m="":l<2&&c.length>=1?m="coords = 0;":m=c.map(h=>`coords.${f[h+p]} = 0;`).join(`
+    `;let u=Le(l),c=UA(r.shapeInfo.logicalShape,e.logicalShape),p=l-i,m,f=["x","y","z","w","u","v"];i===0?m="":l<2&&c.length>=1?m="coords = 0;":m=c.map(h=>`coords.${f[h+p]} = 0;`).join(`
 `);let d="";return l<2&&i>0?d="coords":d=r.shapeInfo.logicalShape.map((h,g)=>`coords.${f[g+p]}`).join(", "),`
-    float ${o}() {
+    float ${n}() {
       ${u} coords = getOutputCoords();
       ${m}
-      return get${n}(${d});
+      return get${o}(${d});
     }
-  `}function Le(r){if(r<=1)return"int";if(r===2)return"ivec2";if(r===3)return"ivec3";if(r===4)return"ivec4";if(r===5)return"ivec5";if(r===6)return"ivec6";throw Error(`GPU for rank ${r} is not yet supported`)}function bp(r,e){let t=JSON.parse(JSON.stringify(r));return t.shapeInfo.logicalShape=e,t}function wp(r,e){return e.map(t=>r[t]).join(", ")}function yE(r,e,t,n){let o=e.userCode,s=t.map((f,d)=>{let h={logicalShape:f.shape,texShape:f.isUniform?null:f.texData.texShape,isUniform:f.isUniform,isPacked:f.isUniform?!1:f.texData.isPacked,flatOffset:null};return f.texData!=null&&f.texData.slice!=null&&f.texData.slice.flatOffset>0&&(h.flatOffset=f.texData.slice.flatOffset),{name:e.variableNames[d],shapeInfo:h}}),a=s.map(f=>f.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},l=hE(s,i,o,e.packedInputs),u=r.createProgram(l),c=null,p=r.getUniformLocation(u,"NAN",!1);j().getNumber("WEBGL_VERSION")===1&&(c=r.getUniformLocation(u,"INFINITY",!1));let m={};for(let f=0;f<e.variableNames.length;f++){let d=e.variableNames[f],h=!1;m[d]=r.getUniformLocation(u,d,h),m[`offset${d}`]=r.getUniformLocation(u,`offset${d}`,h)}return{program:e,source:l,webGLProgram:u,uniformLocations:m,inShapeInfos:a,outShapeInfo:i,infLoc:c,nanLoc:p}}function bE(r,e){if(r.length!==e.length)throw Error(`Binary was compiled with ${r.length} inputs, but was executed with ${e.length} inputs`);r.forEach((t,n)=>{let o=t.logicalShape,s=e[n],a=s.shape;if(!y.arraysEqual(o,a))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${o} and ${a} must match`);if(t.isUniform&&s.isUniform)return;let i=t.texShape,l=s.isUniform?null:s.texData.texShape;if(!y.arraysEqual(i,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${l} must match`)})}function wE(r,e,t,n,o){bE(e.inShapeInfos,t),bE([e.outShapeInfo],[n]);let s=n.texData.texture,a=n.texData.texShape;n.texData.isPacked?r.setOutputPackedMatrixTexture(s,a[0],a[1]):r.setOutputMatrixTexture(s,a[0],a[1]),r.setProgram(e.webGLProgram),j().getNumber("WEBGL_VERSION")===1&&e.infLoc!==null&&r.gl.uniform1f(e.infLoc,Infinity),e.nanLoc!==null&&r.gl.uniform1f(e.nanLoc,NaN),t.forEach((i,l)=>{let u=e.program.variableNames[l],c=e.uniformLocations[u],p=e.uniformLocations[`offset${u}`];if(c!=null){if(i.isUniform){if(y.sizeFromShape(i.shape)<2)r.gl.uniform1f(c,i.uniformValues[0]);else{let m=i.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),r.gl.uniform1fv(c,m)}return}i.texData.slice!=null&&p!=null&&r.gl.uniform1i(p,i.texData.slice.flatOffset),r.setInputMatrixTexture(i.texData.texture,c,l)}}),o!=null&&o(r,e.webGLProgram),r.executeProgram()}function kE(r,e,t){let n="";e.concat(t).forEach(a=>{let i=a.texData!=null&&a.texData.slice!=null&&a.texData.slice.flatOffset>0,l=a.isUniform?"uniform":a.texData.texShape;n+=`${a.shape}_${l}_${i}`});let o=r.userCode,s=r.constructor.name;return s+="_"+n+"_"+o,s}var{addImpl:_E,bincountImpl:Bg,bincountReduceImpl:vE,ceilImpl:CE,concatImpl:IE,expImpl:NE,expm1Impl:SE,floorImpl:TE,gatherV2Impl:AE,greaterImpl:EE,lessImpl:DE,linSpaceImpl:$E,logImpl:RE,maxImpl:FE,maximumImpl:OE,minimumImpl:PE,multiplyImpl:ME,negImpl:LE,prodImpl:zE,rangeImpl:BE,rsqrtImpl:VE,simpleAbsImpl:Vg,sliceImpl:GE,stridedSliceImpl:WE,subImpl:jE,tileImpl:UE,topKImpl:HE,transposeImpl:kp,uniqueImpl:qE}=wg;function E_(r,e){return["x","y","z","w","u","v"].slice(0,e).map(t=>`${r}.${t}`)}function jt(r,e){return e===1?[r]:E_(r,e)}function KE(r,e){if(r===1)return"rc";let t="";for(let n=0;n<r;n++)t+=e[n],n<r-1&&(t+=",");return t}var D_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
+  `}function Le(r){if(r<=1)return"int";if(r===2)return"ivec2";if(r===3)return"ivec3";if(r===4)return"ivec4";if(r===5)return"ivec5";if(r===6)return"ivec6";throw Error(`GPU for rank ${r} is not yet supported`)}function yp(r,e){let t=JSON.parse(JSON.stringify(r));return t.shapeInfo.logicalShape=e,t}function bp(r,e){return e.map(t=>r[t]).join(", ")}function XA(r,e,t,o){let n=e.userCode,s=t.map((f,d)=>{let h={logicalShape:f.shape,texShape:f.isUniform?null:f.texData.texShape,isUniform:f.isUniform,isPacked:f.isUniform?!1:f.texData.isPacked,flatOffset:null};return f.texData!=null&&f.texData.slice!=null&&f.texData.slice.flatOffset>0&&(h.flatOffset=f.texData.slice.flatOffset),{name:e.variableNames[d],shapeInfo:h}}),a=s.map(f=>f.shapeInfo),i={logicalShape:o.shape,texShape:o.texData.texShape,isUniform:!1,isPacked:o.texData.isPacked,flatOffset:null},l=HA(s,i,n,e.packedInputs),u=r.createProgram(l),c=null,p=r.getUniformLocation(u,"NAN",!1);W().getNumber("WEBGL_VERSION")===1&&(c=r.getUniformLocation(u,"INFINITY",!1));let m={};for(let f=0;f<e.variableNames.length;f++){let d=e.variableNames[f],h=!1;m[d]=r.getUniformLocation(u,d,h),m[`offset${d}`]=r.getUniformLocation(u,`offset${d}`,h)}return{program:e,source:l,webGLProgram:u,uniformLocations:m,inShapeInfos:a,outShapeInfo:i,infLoc:c,nanLoc:p}}function YA(r,e){if(r.length!==e.length)throw Error(`Binary was compiled with ${r.length} inputs, but was executed with ${e.length} inputs`);r.forEach((t,o)=>{let n=t.logicalShape,s=e[o],a=s.shape;if(!y.arraysEqual(n,a))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${n} and ${a} must match`);if(t.isUniform&&s.isUniform)return;let i=t.texShape,l=s.isUniform?null:s.texData.texShape;if(!y.arraysEqual(i,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${l} must match`)})}function ZA(r,e,t,o,n){YA(e.inShapeInfos,t),YA([e.outShapeInfo],[o]);let s=o.texData.texture,a=o.texData.texShape;o.texData.isPacked?r.setOutputPackedMatrixTexture(s,a[0],a[1]):r.setOutputMatrixTexture(s,a[0],a[1]),r.setProgram(e.webGLProgram),W().getNumber("WEBGL_VERSION")===1&&e.infLoc!==null&&r.gl.uniform1f(e.infLoc,Infinity),e.nanLoc!==null&&r.gl.uniform1f(e.nanLoc,NaN),t.forEach((i,l)=>{let u=e.program.variableNames[l],c=e.uniformLocations[u],p=e.uniformLocations[`offset${u}`];if(c!=null){if(i.isUniform){if(y.sizeFromShape(i.shape)<2)r.gl.uniform1f(c,i.uniformValues[0]);else{let m=i.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),r.gl.uniform1fv(c,m)}return}i.texData.slice!=null&&p!=null&&r.gl.uniform1i(p,i.texData.slice.flatOffset),r.setInputMatrixTexture(i.texData.texture,c,l)}}),n!=null&&n(r,e.webGLProgram),r.executeProgram()}function JA(r,e,t){let o="";e.concat(t).forEach(a=>{let i=a.texData!=null&&a.texData.slice!=null&&a.texData.slice.flatOffset>0,l=a.isUniform?"uniform":a.texData.texShape;o+=`${a.shape}_${l}_${i}`});let n=r.userCode,s=r.constructor.name;return s+="_"+o+"_"+n,s}var{addImpl:QA,bincountImpl:Mg,bincountReduceImpl:eE,ceilImpl:tE,concatImpl:rE,expImpl:oE,expm1Impl:nE,floorImpl:sE,gatherV2Impl:iE,greaterImpl:aE,lessImpl:lE,linSpaceImpl:uE,logImpl:cE,maxImpl:pE,maximumImpl:mE,minimumImpl:fE,multiplyImpl:dE,negImpl:hE,prodImpl:gE,rangeImpl:xE,rsqrtImpl:yE,simpleAbsImpl:Lg,sliceImpl:bE,stridedSliceImpl:wE,subImpl:kE,tileImpl:_E,topKImpl:vE,transposeImpl:wp,uniqueImpl:CE}=yg;function v_(r,e){return["x","y","z","w","u","v"].slice(0,e).map(t=>`${r}.${t}`)}function Wt(r,e){return e===1?[r]:v_(r,e)}function IE(r,e){if(r===1)return"rc";let t="";for(let o=0;o<r;o++)t+=e[o],o<r-1&&(t+=",");return t}var C_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
         void main() {
           setOutput(vec4(getA(), 0., 0., 0.));
         }
-      `;else{let n=jt("rc",t),o=Le(t),s=B5(t,e,n),a=V5(t,e[e.length-1],e[e.length-2],n),i=G5(e,n);this.userCode=`
+      `;else{let o=Wt("rc",t),n=Le(t),s=p5(t,e,o),a=m5(t,e[e.length-1],e[e.length-2],o),i=f5(e,o);this.userCode=`
         void main() {
-          ${o} rc = getOutputCoords();
+          ${n} rc = getOutputCoords();
 
           if(${s}) {
             setOutput(vec4(0));
@@ -831,33 +831,33 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             setOutput(vec4(${i}));
           }
         }
-      `}}};function W5(r,e){let t=[];for(let n=0;n<=1;n++)for(let o=0;o<=1;o++){let s=`${n===0?"r":"rp1"}, ${o===0?"c":"cp1"}`;for(let a=2;a<r;a++)s=`${e[e.length-1-a]},`+s;t.push(s)}return t}function B5(r,e,t){if(r===1)return`rc > ${e[0]}`;let n="";for(let o=r-2;o<r;o++)n+=`${t[o]} >= ${e[o]}`,o<r-1&&(n+="||");return n}function V5(r,e,t,n){if(r===1)return"";let o=n.slice(-2);return`
-    int r = ${o[0]};
-    int c = ${o[1]};
+      `}}};function d5(r,e){let t=[];for(let o=0;o<=1;o++)for(let n=0;n<=1;n++){let s=`${o===0?"r":"rp1"}, ${n===0?"c":"cp1"}`;for(let a=2;a<r;a++)s=`${e[e.length-1-a]},`+s;t.push(s)}return t}function p5(r,e,t){if(r===1)return`rc > ${e[0]}`;let o="";for(let n=r-2;n<r;n++)o+=`${t[n]} >= ${e[n]}`,n<r-1&&(o+="||");return o}function m5(r,e,t,o){if(r===1)return"";let n=o.slice(-2);return`
+    int r = ${n[0]};
+    int c = ${n[1]};
     int rp1 = r + 1;
     int cp1 = c + 1;
 
     bool cEdge = cp1 >= ${e};
     bool rEdge = rp1 >= ${t};
-  `}function G5(r,e){let t=r.length,n=W5(t,e);return t===1?`getA(rc),
+  `}function f5(r,e){let t=r.length,o=d5(t,e);return t===1?`getA(rc),
             rc + 1 >= ${r[0]} ? 0. : getA(rc + 1),
-            0, 0`:`getA(${n[0]}),
-          cEdge ? 0. : getA(${n[1]}),
-          rEdge ? 0. : getA(${n[2]}),
-          rEdge || cEdge ? 0. : getA(${n[3]})`}var _f=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let o=0;o<4;o++){let s="thisRC = rc;";o%2==1&&(s+="thisRC.z += 1;"),o>1&&(s+="thisRC.y += 1;"),n+=`
+            0, 0`:`getA(${o[0]}),
+          cEdge ? 0. : getA(${o[1]}),
+          rEdge ? 0. : getA(${o[2]}),
+          rEdge || cEdge ? 0. : getA(${o[3]})`}var kf=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let o="";for(let n=0;n<4;n++){let s="thisRC = rc;";n%2==1&&(s+="thisRC.z += 1;"),n>1&&(s+="thisRC.y += 1;"),o+=`
         ${s}
-        ${o>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
+        ${n>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[${o}] =
+          result[${n}] =
             getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
-        ${o>0?"}":""}
+        ${n>0?"}":""}
       `}this.userCode=`
-      ${j5(t)}
-      ${gp(e)}
+      ${h5(t)}
+      ${hp(e)}
 
       void main() {
         ivec3 rc = getOutputCoords();
@@ -868,16 +868,16 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         int rows = ${e[1]};
         int cols = ${e[2]};
 
-        ${n}
+        ${o}
 
         setOutput(result);
       }
-    `}};function j5(r){return`
+    `}};function h5(r){return`
     ivec3 inputCoordsFromReshapedOutCoords(int index) {
       ${Fs(["r","c","d"],r)}
       return ivec3(r, c, d);
     }
-  `}var $_=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let o=YE(t,n),s=ZE(e,o,n);s in this.freeTextures||(this.freeTextures[s]=[]),s in this.usedTextures||(this.usedTextures[s]=[]);let a=XE(e,o,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[s].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let l=this.freeTextures[s].shift();return this.usedTextures[s].push(l),l}let i;return o===_r.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):o===_r.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):o===_r.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):o===_r.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):o===_r.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[s].push(i),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),i}releaseTexture(e,t,n,o){if(this.freeTextures==null)return;let s=YE(n,o),a=ZE(t,s,o);a in this.freeTextures||(this.freeTextures[a]=[]);let i=XE(t,s,this.gpgpu.gl,this.gpgpu.textureConfig,o),l=j().get("WEBGL_DELETE_TEXTURE_THRESHOLD");l!==-1&&this._numBytesAllocated>l?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let u=this.usedTextures[a],c=u.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");u.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function U5(r,e){let t=r;if(e===t.R32F)return 4;if(e===t.R16F)return 2;if(e===t.RGBA32F)return 16;if(e===r.RGBA)return 16;if(e===t.RGBA16F)return 8;throw new Error(`Unknown internal format ${e}`)}function XE(r,e,t,n,o){let s=H5(e,n),a;if(o){let[l,u]=Bi(r[0],r[1]);a=l*u}else{let[l,u]=Yu(r[0],r[1]);a=l*u}let i=U5(t,s);return a*i}function H5(r,e){switch(r){case _r.PACKED_2X2_FLOAT32:return Mg(e);case _r.PACKED_2X2_FLOAT16:return Lg(e);case _r.UNPACKED_FLOAT32:return Fg(e);case _r.UNPACKED_FLOAT16:return Og(e);case _r.PACKED_4X1_UNSIGNED_BYTE:return Pg(e);default:throw new Error(`Unknown physical texture type ${r}`)}}function q5(r){return j().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?r?_r.PACKED_2X2_FLOAT32:_r.UNPACKED_FLOAT32:r?_r.PACKED_2X2_FLOAT16:_r.UNPACKED_FLOAT16}function YE(r,e){if(r===Dr.UPLOAD)return _r.PACKED_2X2_FLOAT32;if(r===Dr.RENDER||r==null)return q5(e);if(r===Dr.DOWNLOAD||r===Dr.PIXELS)return _r.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${r}`)}function ZE(r,e,t){return`${r[0]}_${r[1]}_${e}_${t}`}var ln=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+  `}var I_=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,o){let n=SE(t,o),s=TE(e,n,o);s in this.freeTextures||(this.freeTextures[s]=[]),s in this.usedTextures||(this.usedTextures[s]=[]);let a=NE(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,o);if(this.freeTextures[s].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let l=this.freeTextures[s].shift();return this.usedTextures[s].push(l),l}let i;return n===_r.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===_r.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===_r.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===_r.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===_r.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[s].push(i),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),i}releaseTexture(e,t,o,n){if(this.freeTextures==null)return;let s=SE(o,n),a=TE(t,s,n);a in this.freeTextures||(this.freeTextures[a]=[]);let i=NE(t,s,this.gpgpu.gl,this.gpgpu.textureConfig,n),l=W().get("WEBGL_DELETE_TEXTURE_THRESHOLD");l!==-1&&this._numBytesAllocated>l?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=i):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let u=this.usedTextures[a],c=u.indexOf(e);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");u.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function g5(r,e){let t=r;if(e===t.R32F)return 4;if(e===t.R16F)return 2;if(e===t.RGBA32F)return 16;if(e===r.RGBA)return 16;if(e===t.RGBA16F)return 8;throw new Error(`Unknown internal format ${e}`)}function NE(r,e,t,o,n){let s=x5(e,o),a;if(n){let[l,u]=Bi(r[0],r[1]);a=l*u}else{let[l,u]=Xu(r[0],r[1]);a=l*u}let i=g5(t,s);return a*i}function x5(r,e){switch(r){case _r.PACKED_2X2_FLOAT32:return Fg(e);case _r.PACKED_2X2_FLOAT16:return Og(e);case _r.UNPACKED_FLOAT32:return Dg(e);case _r.UNPACKED_FLOAT16:return $g(e);case _r.PACKED_4X1_UNSIGNED_BYTE:return Rg(e);default:throw new Error(`Unknown physical texture type ${r}`)}}function y5(r){return W().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?r?_r.PACKED_2X2_FLOAT32:_r.UNPACKED_FLOAT32:r?_r.PACKED_2X2_FLOAT16:_r.UNPACKED_FLOAT16}function SE(r,e){if(r===Dr.UPLOAD)return _r.PACKED_2X2_FLOAT32;if(r===Dr.RENDER||r==null)return y5(e);if(r===Dr.DOWNLOAD||r===Dr.PIXELS)return _r.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${r}`)}function TE(r,e,t){return`${r[0]}_${r[1]}_${e}_${t}`}var ao=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       float unaryOperation(float x) {
         ${t}
       }
@@ -888,11 +888,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}},gr="if (isnan(x)) return x;",JE="return x;",R_="return abs(x);";var QE="return (x >= 0.0) ? x : (exp(x) - 1.0);",e2=gr+`
+    `}},gr="if (isnan(x)) return x;",AE="return x;",N_="return abs(x);";var EE="return (x >= 0.0) ? x : (exp(x) - 1.0);",DE=gr+`
   return (x < 0.0) ? 0.0 : x;
-`,t2=gr+`
+`,$E=gr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,vf="return x;";var r2="return x;",n2=`
+`,_f="return x;";var RE="return x;",FE=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -901,7 +901,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,o2=`
+`,OE=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -911,7 +911,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,s2=`
+`,PE=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -932,17 +932,17 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(y);
       }
-    `}};var F_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=jt("rc",t),o=Le(t),s=KE(t,n),a=n.slice(-2),i=t<=1?"rc":`vec2(${a.join(",")})`;this.userCode=`
+    `}};var S_=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,o=Wt("rc",t),n=Le(t),s=IE(t,o),a=o.slice(-2),i=t<=1?"rc":`vec2(${a.join(",")})`;this.userCode=`
       void main() {
-        ${o} rc = getOutputCoords();
+        ${n} rc = getOutputCoords();
         vec4 packedInput = getA(${s});
 
         setOutput(getChannel(packedInput, ${i}));
       }
-    `}};var K5=Ar.whereImpl,X5=1e-7,Y5=1e-4,Gg={};function Z5(r){return r in Gg||(Gg[r]={}),Gg[r]}var J5=128,Q5=600;function e8(){return j().global.screen==null?1024:j().global.screen.height*j().global.screen.width*window.devicePixelRatio*Q5/1024/1024}var Ju=class extends js{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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!j().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Vn(j().getNumber("WEBGL_VERSION"));this.binaryCache=Z5(j().getNumber("WEBGL_VERSION")),this.gpgpu=new zg(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 $_(this.gpgpu),this.numMBBeforeWarning=e8(),this.texData=new Za(this,Mn())}nextDataId(){return Ju.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,n){if((j().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||j().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 o={id:this.nextDataId()};return this.texData.set(o,{shape:t,dtype:n,values:e,usage:Dr.UPLOAD,refCount:1}),o}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,o,s){if(j().getBool("DEBUG")&&this.checkNumericalProblems(t),o==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:o,values:t,usage:Dr.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:o,complexTensorInfos:s,slice:a,shape:i,isPacked:l}=t;if(a!=null){let m;l?m=new Os(i,vf):m=new ln(i,vf);let f=this.runWebGLProgram(m,[{dataId:e,shape:i,dtype:o}],o),d=this.readSync(f.dataId);return this.disposeIntermediateTensorInfo(f),d}if(n!=null)return this.convertAndCacheOnCPU(e);if(o==="string")return n;let u=this.activeTimers!=null,c;u&&(c=y.now());let p;if(o==="complex64"){let m=this.readSync(s.real.dataId),f=this.readSync(s.imag.dataId);p=S.mergeRealAndImagArrays(m,f)}else p=this.getValuesFromTexture(e);return u&&(this.downloadWaitMs+=y.now()-c),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){let d=this.pendingRead.get(e);return new Promise(h=>d.push(h))}let t=this.texData.get(e),{values:n,shape:o,slice:s,dtype:a,complexTensorInfos:i,isPacked:l}=t;if(s!=null){let d;l?d=new Os(o,vf):d=new ln(o,vf);let h=this.runWebGLProgram(d,[{dataId:e,shape:o,dtype:a}],a),g=this.read(h.dataId);return this.disposeIntermediateTensorInfo(h),g}if(n!=null)return this.convertAndCacheOnCPU(e);if(!j().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&j().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let u=null,c;if(a!=="complex64"&&j().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let d=this.texData.get(c.dataId);u=this.gpgpu.createBufferFromTexture(d.texture,...fl(o))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(a==="complex64"){let d=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),h=d[0],g=d[1];p=S.mergeRealAndImagArrays(h,g)}else if(u==null)p=this.getValuesFromTexture(e);else{let d=y.sizeFromShape(o);p=this.gpgpu.downloadFloat32MatrixFromBuffer(u,d)}c!=null&&this.disposeIntermediateTensorInfo(c);let m=this.convertAndCacheOnCPU(e,p),f=this.pendingRead.get(e);return this.pendingRead.delete(e),f.forEach(d=>d(m)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Mn().removeDataId(e,this),this.pendingDeletes--),m}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(o=>y.decodeString(o))}catch(o){throw new Error("Failed to decode encoded string bytes into utf-8")}return ve(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Vk(n))throw j().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:o}=this.texData.get(e),s=y.sizeFromShape(t);if(j().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(e),f=this.texData.get(m.dataId),d=this.gpgpu.downloadMatrixFromPackedTexture(f.texture,...fl(t)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),d}let a=j().getBool("WEBGL_PACK")&&o===!0,i=a?wf(t):t,l=a?new p_(i):new c_(i),u=this.runWebGLProgram(l,[{shape:i,dtype:n,dataId:e}],"float32"),c=this.texData.get(u.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(u),p}timerAvailable(){return j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],o=!1;this.programTimersStack==null?(this.programTimersStack=n,o=!0):this.activeTimers.push(n),this.activeTimers=n,e();let s=y.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),a=y.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,o&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let l=await Promise.all(s);i.kernelMs=y.sum(l),i.getExtraProfileInfo=()=>l.map((u,c)=>({name:a[c],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:y.now(),endMs:null}}endTimer(e){return j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=y.now(),e)}async getQueryTime(e){if(j().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:o,usage:s,isPacked:a,slice:i}=this.texData.get(e),l=i&&i.origDataId||e,u=this.dataRefCount.get(l);u>1?this.dataRefCount.set(l,u-1):(this.dataRefCount.delete(l),t!=null&&(this.numBytesInGPU-=this.computeBytes(o,n),this.textureManager.releaseTexture(t,o,s,a)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return j().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Mn().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=J5){let n=this.getCPUBackend();return!j().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),n!=null&&e.every(o=>this.texData.get(o.dataId).texture==null&&y.sizeFromShape(o.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){S.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return K5(e.shape,t)}packedUnaryOp(e,t,n){let o=new Os(e.shape,t),s=this.compileAndRun(o,[e],n);return Mn().makeTensorFromDataId(s.dataId,s.shape,s.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let o=Vg(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,o)}if(j().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,R_,e.dtype);let t=new ln(e.shape,R_),n=this.compileAndRun(t,[e]);return Mn().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let o;if(t==="string"&&n!=null&&n.length>0&&y.isString(n[0])){let s=n.map(a=>y.encodeString(a));o=this.write(s,e,t)}else o=this.write(n,e,t);return this.texData.get(o).usage=null,{dataId:o,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:o}=this.makeTensorInfo(e,t,n);return Mn().makeTensorFromDataId(o,e,t,this)}unpackTensor(e){let t=new F_(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new D_(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[Oa(e.shape),...Pa(e.shape)],o={dtype:e.dtype,shape:n,dataId:e.dataId},s=[Oa(t),...Pa(t)],a=new _f(s,n),i=!0,l=this.runWebGLProgram(a,[o],e.dtype,null,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:o,dtype:s}=t,a=wf(o),i;n?i=new u_(a):i=new l_(a);let l=!0,u=this.runWebGLProgram(i,[{shape:a,dtype:s,dataId:e}],s,null,l);return{dtype:s,shape:o,dataId:u.dataId}}runWebGLProgram(e,t,n,o,s=!1){let a=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(a.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===ml.DENSE){let g=fl(e.outputShape);i.texShape=g.map(x=>x*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),y.sizeFromShape(a.shape)===0)return i.values=y.getTypedArrayFromDType(a.dtype,0),a;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let x=this.texData.get(g.dataId);if(x.texture==null){if(!e.packedInputs&&y.sizeFromShape(g.shape)<=j().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:x.values};e.packedInputs&&(x.isPacked=!0,x.shape=g.shape)}else if(!!x.isPacked!=!!e.packedInputs)g=x.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),x=this.texData.get(g.dataId);else if(x.isPacked&&!dl(x.shape,g.shape)){let w=g,b=g.shape;g.shape=x.shape,g=this.packedReshape(g,b),l.push(g),x=this.texData.get(g.dataId),w.shape=b}return this.uploadToGPU(g.dataId),{shape:g.shape,texData:x,isUniform:!1}});this.uploadToGPU(a.dataId);let c={shape:a.shape,texData:i,isUniform:!1},p=kE(e,u,c),m=this.getAndSaveBinary(p,()=>yE(this.gpgpu,e,u,c)),f=this.activeTimers!=null,d;f&&(d=this.startTimer()),wE(this.gpgpu,m,u,c,o),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),f&&(d=this.endTimer(d),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(d)}));let h=j().get("WEBGL_FLUSH_THRESHOLD");if(h>0){let g=y.now();g-this.lastGlFlushTime>h&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!j().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&s===!1){let g=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),g}return a}compileAndRun(e,t,n,o,s=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,o,s)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(j().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(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=G(()=>{if(!j().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=j().getBool("DEBUG");j().set("DEBUG",!1);let t=this.abs(le(1e-8)).dataSync()[0];if(j().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?X5:Y5}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:o,values:s,texture:a,usage:i,isPacked:l}=t;if(a!=null)return;let u=this.activeTimers!=null,c;u&&(c=y.now());let p=t.texShape;if(p==null&&(p=e_(n,l),t.texShape=p),s!=null){let m=wf(n),f,d=p[1],h=p[0],g=s instanceof Uint8Array;l?([d,h]=Bi(p[0],p[1]),f=new f_(m,[h,d],g)):f=new m_(m,[h,d],g);let x=this.makeTensorInfo([h,d],o);g?this.texData.get(x.dataId).usage=Dr.PIXELS:this.texData.get(x.dataId).usage=Dr.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(x.dataId),d,h,s);let w=!0,b=this.runWebGLProgram(f,[x],o,null,w),k=this.texData.get(b.dataId);t.texture=k.texture,t.texShape=k.texShape,t.isPacked=k.isPacked,t.usage=k.usage,this.disposeIntermediateTensorInfo(x),this.texData.delete(b.dataId),t.values=null,u&&(this.uploadWaitMs+=y.now()-c)}else{let m=this.acquireTexture(p,i,o,l);t.texture=m}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:o}=n;return this.releaseGPUData(e),t!=null&&(n.values=t8(t,o)),n.values}acquireTexture(e,t,n,o){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,o)}computeBytes(e,t){return e[0]*e[1]*y.bytesPerElement(t)}};Ju.nextDataId=0;function t8(r,e){if(e==="float32"||e==="complex64")return r;if(e==="int32"||e==="bool"){let t=e==="int32"?new Int32Array(r.length):new Uint8Array(r.length);for(let n=0;n<t.length;++n)t[n]=Math.round(r[n]);return t}else throw new Error(`Unknown dtype ${e}`)}var O_="3.3.0";function P_(){j().set("WEBGL_FORCE_F16_TEXTURES",!0)}hu.isBrowser()&&xu("webgl",()=>new Ju,2);var r8={forceHalfFloat:P_};var Wg=`
+    `}};var b5=Ar.whereImpl,w5=1e-7,k5=1e-4,zg={};function _5(r){return r in zg||(zg[r]={}),zg[r]}var v5=128,C5=600;function I5(){return W().global.screen==null?1024:W().global.screen.height*W().global.screen.width*window.devicePixelRatio*C5/1024/1024}var Zu=class extends js{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.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!W().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=Vo(W().getNumber("WEBGL_VERSION"));this.binaryCache=_5(W().getNumber("WEBGL_VERSION")),this.gpgpu=new Pg(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 I_(this.gpgpu),this.numMBBeforeWarning=I5(),this.texData=new Za(this,Mo())}nextDataId(){return Zu.nextDataId++}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(e,t,o){if((W().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||W().getBool("DEBUG"))&&this.checkNumericalProblems(e),o==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let n={id:this.nextDataId()};return this.texData.set(n,{shape:t,dtype:o,values:e,usage:Dr.UPLOAD,refCount:1}),n}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,o,n,s){if(W().getBool("DEBUG")&&this.checkNumericalProblems(t),n==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:o,dtype:n,values:t,usage:Dr.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:o,dtype:n,complexTensorInfos:s,slice:a,shape:i,isPacked:l}=t;if(a!=null){let m;l?m=new Os(i,_f):m=new ao(i,_f);let f=this.runWebGLProgram(m,[{dataId:e,shape:i,dtype:n}],n),d=this.readSync(f.dataId);return this.disposeIntermediateTensorInfo(f),d}if(o!=null)return this.convertAndCacheOnCPU(e);if(n==="string")return o;let u=this.activeTimers!=null,c;u&&(c=y.now());let p;if(n==="complex64"){let m=this.readSync(s.real.dataId),f=this.readSync(s.imag.dataId);p=N.mergeRealAndImagArrays(m,f)}else p=this.getValuesFromTexture(e);return u&&(this.downloadWaitMs+=y.now()-c),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){let d=this.pendingRead.get(e);return new Promise(h=>d.push(h))}let t=this.texData.get(e),{values:o,shape:n,slice:s,dtype:a,complexTensorInfos:i,isPacked:l}=t;if(s!=null){let d;l?d=new Os(n,_f):d=new ao(n,_f);let h=this.runWebGLProgram(d,[{dataId:e,shape:n,dtype:a}],a),g=this.read(h.dataId);return this.disposeIntermediateTensorInfo(h),g}if(o!=null)return this.convertAndCacheOnCPU(e);if(!W().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&W().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let u=null,c;if(a!=="complex64"&&W().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(e);let d=this.texData.get(c.dataId);u=this.gpgpu.createBufferFromTexture(d.texture,...fl(n))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(a==="complex64"){let d=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),h=d[0],g=d[1];p=N.mergeRealAndImagArrays(h,g)}else if(u==null)p=this.getValuesFromTexture(e);else{let d=y.sizeFromShape(n);p=this.gpgpu.downloadFloat32MatrixFromBuffer(u,d)}c!=null&&this.disposeIntermediateTensorInfo(c);let m=this.convertAndCacheOnCPU(e,p),f=this.pendingRead.get(e);return this.pendingRead.delete(e),f.forEach(d=>d(m)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Mo().removeDataId(e,this),this.pendingDeletes--),m}bufferSync(e){let t=this.readSync(e.dataId),o=t;if(e.dtype==="string")try{o=t.map(n=>y.decodeString(n))}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return ve(e.shape,e.dtype,o)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let o=e[t];if(!Fk(o))throw W().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${o} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${o} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:o,isPacked:n}=this.texData.get(e),s=y.sizeFromShape(t);if(W().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(e),f=this.texData.get(m.dataId),d=this.gpgpu.downloadMatrixFromPackedTexture(f.texture,...fl(t)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),d}let a=W().getBool("WEBGL_PACK")&&n===!0,i=a?bf(t):t,l=a?new n_(i):new o_(i),u=this.runWebGLProgram(l,[{shape:i,dtype:o,dataId:e}],"float32"),c=this.texData.get(u.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(u),p}timerAvailable(){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,o=[],n=!1;this.programTimersStack==null?(this.programTimersStack=o,n=!0):this.activeTimers.push(o),this.activeTimers=o,e();let s=y.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),a=y.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let l=await Promise.all(s);i.kernelMs=y.sum(l),i.getExtraProfileInfo=()=>l.map((u,c)=>({name:a[c],ms:u})).map(u=>`${u.name}: ${u.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:y.now(),endMs:null}}endTimer(e){return W().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=y.now(),e)}async getQueryTime(e){if(W().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:o}=this.texData.get(e);return o!=null&&(this.disposeData(o.real.dataId,t),this.disposeData(o.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:o,texShape:n,usage:s,isPacked:a,slice:i}=this.texData.get(e),l=i&&i.origDataId||e,u=this.dataRefCount.get(l);u>1?this.dataRefCount.set(l,u-1):(this.dataRefCount.delete(l),t!=null&&(this.numBytesInGPU-=this.computeBytes(n,o),this.textureManager.releaseTexture(t,n,s,a)));let c=this.texData.get(e);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return W().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Mo().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=v5){let o=this.getCPUBackend();return!W().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&o==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. Consider importing the CPU backend (@tensorflow/tfjs-backend-cpu) for better performance."),this.warnedAboutCPUBackend=!0),o!=null&&e.every(n=>this.texData.get(n.dataId).texture==null&&y.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){N.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return b5(e.shape,t)}packedUnaryOp(e,t,o){let n=new Os(e.shape,t),s=this.compileAndRun(n,[e],o);return Mo().makeTensorFromDataId(s.dataId,s.shape,s.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let n=Lg(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,n)}if(W().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,N_,e.dtype);let t=new ao(e.shape,N_),o=this.compileAndRun(t,[e]);return Mo().makeTensorFromDataId(o.dataId,o.shape,o.dtype)}makeTensorInfo(e,t,o){let n;if(t==="string"&&o!=null&&o.length>0&&y.isString(o[0])){let s=o.map(a=>y.encodeString(a));n=this.write(s,e,t)}else n=this.write(o,e,t);return this.texData.get(n).usage=null,{dataId:n,shape:e,dtype:t}}makeOutput(e,t,o){let{dataId:n}=this.makeTensorInfo(e,t,o);return Mo().makeTensorFromDataId(n,e,t,this)}unpackTensor(e){let t=new S_(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new C_(e.shape),o=!0;return this.runWebGLProgram(t,[e],e.dtype,null,o)}packedReshape(e,t){let o=[Oa(e.shape),...Pa(e.shape)],n={dtype:e.dtype,shape:o,dataId:e.dataId},s=[Oa(t),...Pa(t)],a=new kf(s,o),i=!0,l=this.runWebGLProgram(a,[n],e.dtype,null,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e){let t=this.texData.get(e),{isPacked:o,shape:n,dtype:s}=t,a=bf(n),i;o?i=new r_(a):i=new t_(a);let l=!0,u=this.runWebGLProgram(i,[{shape:a,dtype:s,dataId:e}],s,null,l);return{dtype:s,shape:n,dataId:u.dataId}}runWebGLProgram(e,t,o,n,s=!1){let a=this.makeTensorInfo(e.outputShape,o),i=this.texData.get(a.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===ml.DENSE){let g=fl(e.outputShape);i.texShape=g.map(x=>x*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),y.sizeFromShape(a.shape)===0)return i.values=y.getTypedArrayFromDType(a.dtype,0),a;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let x=this.texData.get(g.dataId);if(x.texture==null){if(!e.packedInputs&&y.sizeFromShape(g.shape)<=W().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:x.values};e.packedInputs&&(x.isPacked=!0,x.shape=g.shape)}else if(!!x.isPacked!=!!e.packedInputs)g=x.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),x=this.texData.get(g.dataId);else if(x.isPacked&&!dl(x.shape,g.shape)){let b=g,w=g.shape;g.shape=x.shape,g=this.packedReshape(g,w),l.push(g),x=this.texData.get(g.dataId),b.shape=w}return this.uploadToGPU(g.dataId),{shape:g.shape,texData:x,isUniform:!1}});this.uploadToGPU(a.dataId);let c={shape:a.shape,texData:i,isUniform:!1},p=JA(e,u,c),m=this.getAndSaveBinary(p,()=>XA(this.gpgpu,e,u,c)),f=this.activeTimers!=null,d;f&&(d=this.startTimer()),ZA(this.gpgpu,m,u,c,n),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),f&&(d=this.endTimer(d),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(d)}));let h=W().get("WEBGL_FLUSH_THRESHOLD");if(h>0){let g=y.now();g-this.lastGlFlushTime>h&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!W().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&s===!1){let g=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),g}return a}compileAndRun(e,t,o,n,s=!1){return o=o||t[0].dtype,this.runWebGLProgram(e,t,o,n,s)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(W().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=V(()=>{if(!W().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=W().getBool("DEBUG");W().set("DEBUG",!1);let t=this.abs(le(1e-8)).dataSync()[0];if(W().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?w5:k5}uploadToGPU(e){let t=this.texData.get(e),{shape:o,dtype:n,values:s,texture:a,usage:i,isPacked:l}=t;if(a!=null)return;let u=this.activeTimers!=null,c;u&&(c=y.now());let p=t.texShape;if(p==null&&(p=qk(o,l),t.texShape=p),s!=null){let m=bf(o),f,d=p[1],h=p[0],g=s instanceof Uint8Array;l?([d,h]=Bi(p[0],p[1]),f=new i_(m,[h,d],g)):f=new s_(m,[h,d],g);let x=this.makeTensorInfo([h,d],n);g?this.texData.get(x.dataId).usage=Dr.PIXELS:this.texData.get(x.dataId).usage=Dr.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(x.dataId),d,h,s);let b=!0,w=this.runWebGLProgram(f,[x],n,null,b),k=this.texData.get(w.dataId);t.texture=k.texture,t.texShape=k.texShape,t.isPacked=k.isPacked,t.usage=k.usage,this.disposeIntermediateTensorInfo(x),this.texData.delete(w.dataId),t.values=null,u&&(this.uploadWaitMs+=y.now()-c)}else{let m=this.acquireTexture(p,i,n,l);t.texture=m}}convertAndCacheOnCPU(e,t){let o=this.texData.get(e),{dtype:n}=o;return this.releaseGPUData(e),t!=null&&(o.values=N5(t,n)),o.values}acquireTexture(e,t,o,n){if(this.numBytesInGPU+=this.computeBytes(e,o),!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,n)}computeBytes(e,t){return e[0]*e[1]*y.bytesPerElement(t)}};Zu.nextDataId=0;function N5(r,e){if(e==="float32"||e==="complex64")return r;if(e==="int32"||e==="bool"){let t=e==="int32"?new Int32Array(r.length):new Uint8Array(r.length);for(let o=0;o<t.length;++o)t[o]=Math.round(r[o]);return t}else throw new Error(`Unknown dtype ${e}`)}var T_="3.3.0";function A_(){W().set("WEBGL_FORCE_F16_TEXTURES",!0)}hu.isBrowser()&&xu("webgl",()=>new Zu,2);var S5={forceHalfFloat:A_};var Bg=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`;var Xo=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=S.assertAndGetBroadcastShape(t,n),this.userCode=`
+`;var Xn=class{constructor(e,t,o){this.variableNames=["A","B"],this.outputShape=N.assertAndGetBroadcastShape(t,o),this.userCode=`
       float binaryOperation(float a, float b) {
         ${e}
       }
@@ -957,7 +957,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.g = isNaN.g > 0. ? NAN : result.g;
   result.b = isNaN.b > 0. ? NAN : result.b;
   result.a = isNaN.a > 0. ? NAN : result.a;
-`;var Ps=class{constructor(e,t,n,o=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=S.assertAndGetBroadcastShape(t,n);let s=this.outputShape.length,a="";if(o)if(s===0||y.sizeFromShape(this.outputShape)===1)a=`
+`;var Ps=class{constructor(e,t,o,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=N.assertAndGetBroadcastShape(t,o);let s=this.outputShape.length,a="";if(n)if(s===0||y.sizeFromShape(this.outputShape)===1)a=`
           result.y = 0.;
           result.z = 0.;
           result.w = 0.;
@@ -967,7 +967,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
             result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
             result.z = 0.;
             result.w = 0.;
-          `;else{let l=jt("coords",s);a+=`
+          `;else{let l=Wt("coords",s);a+=`
             bool nextRowOutOfBounds =
               (${l[s-2]} + 1) >= ${this.outputShape[s-2]};
             bool nextColOutOfBounds =
@@ -989,21 +989,21 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function Ut(r){let{inputs:e,backend:t}=r,{x:n}=e;return t.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var i2={kernelName:Fn,backendName:"webgl",kernelFunc:Ut};function un(r){let{inputs:e,backend:t}=r,{real:n,imag:o}=e,s=t.makeTensorInfo(n.shape,"complex64"),a=t.texData.get(s.dataId),i=Ut({inputs:{x:n},backend:t}),l=Ut({inputs:{x:o},backend:t});return a.complexTensorInfos={real:i,imag:l},s}var a2={kernelName:Gl,backendName:"webgl",kernelFunc:un};var M_="return (a < 0.) ? b * a : a;",L_=`
+    `}};function jt(r){let{inputs:e,backend:t}=r,{x:o}=e;return t.incRef(o.dataId),{dataId:o.dataId,shape:o.shape,dtype:o.dtype}}var ME={kernelName:Fo,backendName:"webgl",kernelFunc:jt};function lo(r){let{inputs:e,backend:t}=r,{real:o,imag:n}=e,s=t.makeTensorInfo(o.shape,"complex64"),a=t.texData.get(s.dataId),i=jt({inputs:{x:o},backend:t}),l=jt({inputs:{x:n},backend:t});return a.complexTensorInfos={real:i,imag:l},s}var LE={kernelName:Gl,backendName:"webgl",kernelFunc:lo};var E_="return (a < 0.) ? b * a : a;",D_=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function n8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{alpha:s}=n,a=t.makeTensorInfo([],"float32",y.createScalarValue(s,"float32")),i=j().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ps(L_,o.shape,a.shape):new Xo(M_,o.shape,a.shape),l=t.runWebGLProgram(i,[o,a],o.dtype);return t.disposeIntermediateTensorInfo(a),l}var l2={kernelName:lo,backendName:"webgl",kernelFunc:n8};var z_="return (a < 0.) ? b * a : a;",B_=`
+`;function T5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{alpha:s}=o,a=t.makeTensorInfo([],"float32",y.createScalarValue(s,"float32")),i=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ps(D_,n.shape,a.shape):new Xn(E_,n.shape,a.shape),l=t.runWebGLProgram(i,[n,a],n.dtype);return t.disposeIntermediateTensorInfo(a),l}var zE={kernelName:un,backendName:"webgl",kernelFunc:T5};var $_="return (a < 0.) ? b * a : a;",R_=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function o8(r){let{inputs:e,backend:t}=r,{x:n,alpha:o}=e,s=j().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ps(B_,n.shape,o.shape):new Xo(z_,n.shape,o.shape);return t.runWebGLProgram(s,[n,o],n.dtype)}var u2={kernelName:ko,backendName:"webgl",kernelFunc:o8};var jg="if (isnan(x)) return x;",c2=`
+`;function A5(r){let{inputs:e,backend:t}=r,{x:o,alpha:n}=e,s=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ps(R_,o.shape,n.shape):new Xn($_,o.shape,n.shape);return t.runWebGLProgram(s,[o,n],o.dtype)}var BE={kernelName:kn,backendName:"webgl",kernelFunc:A5};var Vg="if (isnan(x)) return x;",VE=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,p2=`
+`,GE=`
   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 ke({opSnippet:r,packedOpSnippet:e,cpuKernelImpl:t,dtype:n}){return({inputs:o,backend:s})=>{let{x:a}=o,i=s,l=n||a.dtype;if(i.shouldExecuteOnCPU([a])&&t!=null){let p=i.texData.get(a.dataId),m=t(p.values,l);return i.makeTensorInfo(a.shape,l,m)}let u=j().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&e!=null,c;return u?c=new Os(a.shape,e):c=new ln(a.shape,r),i.runWebGLProgram(c,[a],l)}}function ot({opSnippet:r,packedOpSnippet:e,checkOutOfBounds:t=!1,supportsComplex:n=!1,cpuKernelImpl:o,dtype:s}){return({inputs:a,backend:i})=>{let{a:l,b:u}=a,c=i;if(n&&l.dtype==="complex64"){let d=c.texData.get(l.dataId),h=c.texData.get(u.dataId),[g,x]=[[d.complexTensorInfos.real,h.complexTensorInfos.real],[d.complexTensorInfos.imag,h.complexTensorInfos.imag]].map(b=>{let[k,_]=b,A={dataId:k.dataId,dtype:k.dtype,shape:l.shape},N={dataId:_.dataId,dtype:_.dtype,shape:u.shape},$=new Xo(r,l.shape,u.shape);return c.runWebGLProgram($,[A,N],dr(k.dtype,_.dtype))}),w=un({inputs:{real:g,imag:x},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(x),w}let p=s||dr(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&o!=null){let d=c.texData.get(l.dataId),h=c.texData.get(u.dataId),[g,x]=o(l.shape,u.shape,d.values,h.values,p),w=c.makeTensorInfo(x,p),b=c.texData.get(w.dataId);return b.values=g,w}let m=j().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&e!=null,f;return m?f=new Ps(e,l.shape,u.shape,t):f=new Xo(r,l.shape,u.shape),c.runWebGLProgram(f,[l,u],p)}}function gl(r,e=!1){if(r==="linear")return e?r2:JE;if(r==="relu")return e?o2:e2;if(r==="elu")return e?n2:QE;if(r==="relu6")return e?s2:t2;if(r==="prelu")return e?B_:z_;if(r==="leakyrelu")return e?L_:M_;throw new Error(`Activation ${r} has not been implemented for the WebGL backend.`)}var Cf=class{constructor(e,t,n,o=!1,s=!1,a=!1,i=null,l=!1,u=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let c=o?e[1]:e[2],p=Math.ceil(c/2),m=o?"i * 2, rc.y":"rc.y, i * 2",f=s?"rc.z, i * 2":"i * 2, rc.z",d=o?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],h=s?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],g="",x="";i&&(l?g=`vec4 activation(vec4 a) {
+`;function ke({opSnippet:r,packedOpSnippet:e,cpuKernelImpl:t,dtype:o}){return({inputs:n,backend:s})=>{let{x:a}=n,i=s,l=o||a.dtype;if(i.shouldExecuteOnCPU([a])&&t!=null){let p=i.texData.get(a.dataId),m=t(p.values,l);return i.makeTensorInfo(a.shape,l,m)}let u=W().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&e!=null,c;return u?c=new Os(a.shape,e):c=new ao(a.shape,r),i.runWebGLProgram(c,[a],l)}}function nt({opSnippet:r,packedOpSnippet:e,checkOutOfBounds:t=!1,supportsComplex:o=!1,cpuKernelImpl:n,dtype:s}){return({inputs:a,backend:i})=>{let{a:l,b:u}=a,c=i;if(o&&l.dtype==="complex64"){let d=c.texData.get(l.dataId),h=c.texData.get(u.dataId),[g,x]=[[d.complexTensorInfos.real,h.complexTensorInfos.real],[d.complexTensorInfos.imag,h.complexTensorInfos.imag]].map(w=>{let[k,_]=w,D={dataId:k.dataId,dtype:k.dtype,shape:l.shape},T={dataId:_.dataId,dtype:_.dtype,shape:u.shape},R=new Xn(r,l.shape,u.shape);return c.runWebGLProgram(R,[D,T],dr(k.dtype,_.dtype))}),b=lo({inputs:{real:g,imag:x},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(x),b}let p=s||dr(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&n!=null){let d=c.texData.get(l.dataId),h=c.texData.get(u.dataId),[g,x]=n(l.shape,u.shape,d.values,h.values,p),b=c.makeTensorInfo(x,p),w=c.texData.get(b.dataId);return w.values=g,b}let m=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&e!=null,f;return m?f=new Ps(e,l.shape,u.shape,t):f=new Xn(r,l.shape,u.shape),c.runWebGLProgram(f,[l,u],p)}}function gl(r,e=!1){if(r==="linear")return e?RE:AE;if(r==="relu")return e?OE:DE;if(r==="elu")return e?FE:EE;if(r==="relu6")return e?PE:$E;if(r==="prelu")return e?R_:$_;if(r==="leakyrelu")return e?D_:E_;throw new Error(`Activation ${r} has not been implemented for the WebGL backend.`)}var vf=class{constructor(e,t,o,n=!1,s=!1,a=!1,i=null,l=!1,u=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=o;let c=n?e[1]:e[2],p=Math.ceil(c/2),m=n?"i * 2, rc.y":"rc.y, i * 2",f=s?"rc.z, i * 2":"i * 2, rc.z",d=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],h=s?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],g="",x="";i&&(l?g=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${i}
         }`:u?g=`vec4 activation(vec4 a) {
@@ -1011,7 +1011,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           ${i}
         }`:g=`vec4 activation(vec4 x) {
           ${i}
-        }`,x="result = activation(result);");let w=a?"result += getBiasAtOutCoords();":"";a&&this.variableNames.push("bias"),l&&this.variableNames.push("preluActivationWeights"),u&&this.variableNames.push("leakyreluAlpha");let b="rc.x",k="rc.x";e[0]<t[0]?b=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(k=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
+        }`,x="result = activation(result);");let b=a?"result += getBiasAtOutCoords();":"";a&&this.variableNames.push("bias"),l&&this.variableNames.push("preluActivationWeights"),u&&this.variableNames.push("leakyreluAlpha");let w="rc.x",k="rc.x";e[0]<t[0]?w=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(k=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
       ${g}
 
       const float sharedDimension = ${p}.0;
@@ -1019,7 +1019,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec4 dot2x2ARowBCol(ivec3 rc) {
         vec4 result = vec4(0);
         for (int i = 0; i < ${p}; i++) {
-          int batchA = ${b};
+          int batchA = ${w};
           int batchB = ${k};
           vec4 a = getMatrixA(batchA, ${m});
           vec4 b = getMatrixB(batchB, ${f});
@@ -1036,13 +1036,13 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         ivec3 rc = getOutputCoords();
         vec4 result = dot2x2ARowBCol(rc);
 
-        ${w}
+        ${b}
 
         ${x}
 
         setOutput(result);
       }
-    `}};var V_={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Ug=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=S.assertAndGetBroadcastShape(t,n),this.userCode=`
+    `}};var F_={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Gg=class{constructor(e,t,o){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=N.assertAndGetBroadcastShape(t,o),this.userCode=`
       float binaryOpComplex(
           float areal, float aimag, float breal, float bimag) {
         ${e}
@@ -1055,7 +1055,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float bimag = getBImagAtOutCoords();
         setOutput(binaryOpComplex(areal, aimag, breal, bimag));
       }
-    `}};var m2="return a * b;";function G_(r){let{inputs:e,backend:t}=r,{a:n,b:o}=e,s=S.upcastType(n.dtype,o.dtype);if(n.dtype==="complex64"){let i=t.texData.get(n.dataId),l=t.texData.get(o.dataId),u=new Ug(V_.REAL,n.shape,o.shape),c=new Ug(V_.IMAG,n.shape,o.shape),p=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:n.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:o.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:o.shape}],m=t.runWebGLProgram(u,p,"float32"),f=t.runWebGLProgram(c,p,"float32"),d=un({inputs:{real:m,imag:f},backend:t});return t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f),d}if(t.shouldExecuteOnCPU([n,o])){let i=t.texData.get(n.dataId),l=t.texData.get(o.dataId),[u,c]=ME(n.shape,o.shape,i.values,l.values,s),p=t.makeTensorInfo(c,s),m=t.texData.get(p.dataId);return m.values=u,p}let a;return j().getBool("WEBGL_PACK_BINARY_OPERATIONS")?a=new Ps(m2,n.shape,o.shape):a=new Xo(m2,n.shape,o.shape),t.runWebGLProgram(a,[n,o],s)}var f2={kernelName:xo,backendName:"webgl",kernelFunc:G_};function d2(r,e,t){let n=[Oa(r.shape),...Pa(r.shape)],o={dtype:r.dtype,shape:n,dataId:r.dataId},s=[Oa(e),...Pa(e)],a=new _f(s,n),i=!0,l=t.runWebGLProgram(a,[o],r.dtype,null,i);return{dataId:l.dataId,shape:e,dtype:l.dtype}}function pe(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{shape:s}=n,a=t,i=y.sizeFromShape(o.shape),l=y.inferFromImplicitShape(s,i),u=y.sizeFromShape(l);y.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${o.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=a.texData.get(o.dataId);return c.isPacked&&!dl(o.shape,l)&&!(c.texture!==null&&dl(c.shape,l))?d2(o,l,a):(a.incRef(o.dataId),{dataId:o.dataId,shape:l,dtype:o.dtype})}var h2={kernelName:ds,backendName:"webgl",kernelFunc:pe};var Hg=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:o,inSize:s,outSize:a}=e;this.outputShape=[o,a];let i=Math.floor(n/4)*4,l=n%4,u="sumValue += dot(values, ones);";if(t!=null){let p=1/t;u=`sumValue += dot(values * ${y.isInt(p)?p.toPrecision(2):p}, ones);`}let c="";s%n>0&&(c=`
+    `}};var WE="return a * b;";function O_(r){let{inputs:e,backend:t}=r,{a:o,b:n}=e,s=N.upcastType(o.dtype,n.dtype);if(o.dtype==="complex64"){let i=t.texData.get(o.dataId),l=t.texData.get(n.dataId),u=new Gg(F_.REAL,o.shape,n.shape),c=new Gg(F_.IMAG,o.shape,n.shape),p=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:o.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:o.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:n.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:n.shape}],m=t.runWebGLProgram(u,p,"float32"),f=t.runWebGLProgram(c,p,"float32"),d=lo({inputs:{real:m,imag:f},backend:t});return t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f),d}if(t.shouldExecuteOnCPU([o,n])){let i=t.texData.get(o.dataId),l=t.texData.get(n.dataId),[u,c]=dE(o.shape,n.shape,i.values,l.values,s),p=t.makeTensorInfo(c,s),m=t.texData.get(p.dataId);return m.values=u,p}let a;return W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?a=new Ps(WE,o.shape,n.shape):a=new Xn(WE,o.shape,n.shape),t.runWebGLProgram(a,[o,n],s)}var jE={kernelName:xn,backendName:"webgl",kernelFunc:O_};function UE(r,e,t){let o=[Oa(r.shape),...Pa(r.shape)],n={dtype:r.dtype,shape:o,dataId:r.dataId},s=[Oa(e),...Pa(e)],a=new kf(s,o),i=!0,l=t.runWebGLProgram(a,[n],r.dtype,null,i);return{dataId:l.dataId,shape:e,dtype:l.dtype}}function pe(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{shape:s}=o,a=t,i=y.sizeFromShape(n.shape),l=y.inferFromImplicitShape(s,i),u=y.sizeFromShape(l);y.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${n.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=a.texData.get(n.dataId);return c.isPacked&&!dl(n.shape,l)&&!(c.texture!==null&&dl(c.shape,l))?UE(n,l,a):(a.incRef(n.dataId),{dataId:n.dataId,shape:l,dtype:n.dtype})}var HE={kernelName:ds,backendName:"webgl",kernelFunc:pe};var Wg=class{constructor(e,t){this.variableNames=["x"];let{windowSize:o,batchSize:n,inSize:s,outSize:a}=e;this.outputShape=[n,a];let i=Math.floor(o/4)*4,l=o%4,u="sumValue += dot(values, ones);";if(t!=null){let p=1/t;u=`sumValue += dot(values * ${y.isInt(p)?p.toPrecision(2):p}, ones);`}let c="";s%o>0&&(c=`
         if (inIdx < 0 || inIdx >= ${s}) {
           return 0.0;
         }
@@ -1071,7 +1071,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int outIdx = coords[1];
-        int inOffset = outIdx * ${n};
+        int inOffset = outIdx * ${o};
 
         float sumValue = 0.0;
 
@@ -1108,7 +1108,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(sumValue);
       }
-    `}};var W_=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:o,inSize:s,outSize:a}=e;this.outputShape=[o,a];let i="0.0",l="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",l="min"):t==="max"&&(i="-1.0 / 1e-20",l="max");let u=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?u="sumValue":t==="prod"?u="prodValue":t==="all"?u="allValue":t==="any"&&(u="anyValue");let c=Math.floor(n/4)*4,p=n%4,m=`
+    `}};var P_=class{constructor(e,t){this.variableNames=["x"];let{windowSize:o,batchSize:n,inSize:s,outSize:a}=e;this.outputShape=[n,a];let i="0.0",l="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",l="min"):t==="max"&&(i="-1.0 / 1e-20",l="max");let u=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?u="sumValue":t==="prod"?u="prodValue":t==="all"?u="allValue":t==="any"&&(u="anyValue");let c=Math.floor(o/4)*4,p=o%4,m=`
       if (${t==="sum"}) {
         sumValue += dot(values, ones);
       } else if (${t==="prod"}) {
@@ -1125,7 +1125,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         bool reducedAnyValue = any(values);
         float floatedReducedAnyValue = float(reducedAnyValue);
         anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
-      `,f="bvec4");let d="";s%n>0&&(d=`
+      `,f="bvec4");let d="";s%o>0&&(d=`
         if (inIdx < 0 || inIdx >= ${s}) {
           return initializationValue;
         }
@@ -1142,7 +1142,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int outIdx = coords[1];
-        int inOffset = outIdx * ${n};
+        int inOffset = outIdx * ${o};
 
         vec4 minMaxValue = vec4(${i});
         float prodValue = 1.0;
@@ -1193,21 +1193,21 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(${u});
       }
-    `}};function s8(r){let e=[];for(;e.length===0||e[e.length-1].outSize!==1;){let t=e.length?e[e.length-1].outSize:r[1],n=S.computeOptimalWindowSize(t);e.push({inSize:t,windowSize:n,outSize:Math.ceil(t/n)})}return e}function Nn(r,e,t,n){let o=s8(r.shape),s=r;for(let a=0;a<o.length;a++){let{inSize:i,windowSize:l,outSize:u}=o[a],c,p;t==="mean"?c=a===0?new Hg({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u},i):new Hg({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u}):c=new W_({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u},t),p=s,s=n.runWebGLProgram(c,[s],e),p.dataId!==r.dataId&&n.disposeIntermediateTensorInfo(p)}return s}var j_=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 o=Le(this.rank),s=i8(t);this.userCode=`
+    `}};function E5(r){let e=[];for(;e.length===0||e[e.length-1].outSize!==1;){let t=e.length?e[e.length-1].outSize:r[1],o=N.computeOptimalWindowSize(t);e.push({inSize:t,windowSize:o,outSize:Math.ceil(t/o)})}return e}function No(r,e,t,o){let n=E5(r.shape),s=r;for(let a=0;a<n.length;a++){let{inSize:i,windowSize:l,outSize:u}=n[a],c,p;t==="mean"?c=a===0?new Wg({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u},i):new Wg({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u}):c=new P_({windowSize:l,inSize:i,batchSize:r.shape[0],outSize:u},t),p=s,s=o.runWebGLProgram(c,[s],e),p.dataId!==r.dataId&&o.disposeIntermediateTensorInfo(p)}return s}var M_=class{constructor(e,t){this.variableNames=["A"];let o=new Array(e.length);for(let a=0;a<o.length;a++)o[a]=e[t[a]];this.outputShape=o,this.rank=o.length;let n=Le(this.rank),s=D5(t);this.userCode=`
     void main() {
-      ${o} resRC = getOutputCoords();
+      ${n} resRC = getOutputCoords();
       setOutput(getA(${s}));
     }
-    `}};function i8(r){let e=r.length;if(e>6)throw Error(`Transpose for rank ${e} is not yet supported`);let t=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],n=new Array(e);for(let o=0;o<r.length;o++)n[r[o]]=t[o];return n.join()}var U_=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let c=0;c<n.length;c++)n[c]=e[t[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let o=Le(this.rank),s=E_("rc",this.rank),a=new Array(this.rank);for(let c=0;c<t.length;c++)a[t[c]]=s[c];let i=`vec2(${a.slice(-2).join()})`,l=`++${s[this.rank-1]} < ${n[this.rank-1]}`,u=`getChannel(getA(${a.join()}), ${i})`;this.userCode=`
+    `}};function D5(r){let e=r.length;if(e>6)throw Error(`Transpose for rank ${e} is not yet supported`);let t=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],o=new Array(e);for(let n=0;n<r.length;n++)o[r[n]]=t[n];return o.join()}var L_=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let o=new Array(e.length);for(let c=0;c<o.length;c++)o[c]=e[t[c]];if(this.outputShape=o,this.rank=o.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let n=Le(this.rank),s=v_("rc",this.rank),a=new Array(this.rank);for(let c=0;c<t.length;c++)a[t[c]]=s[c];let i=`vec2(${a.slice(-2).join()})`,l=`++${s[this.rank-1]} < ${o[this.rank-1]}`,u=`getChannel(getA(${a.join()}), ${i})`;this.userCode=`
     void main() {
-      ${o} rc = getOutputCoords();
+      ${n} rc = getOutputCoords();
       vec4 result = vec4(0.);
       result[0] = ${u};
       if(${l}) {
         result[1] = ${u};
       }
       --${s[this.rank-1]};
-      if(++${s[this.rank-2]} < ${n[this.rank-2]}) {
+      if(++${s[this.rank-2]} < ${o[this.rank-2]}) {
         result[2] = ${u};
         if(${l}) {
           result[3] = ${u};
@@ -1215,40 +1215,40 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       }
       setOutput(result);
     }
-    `}};function xl(r,e,t){let n=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new U_(r.shape,e):new j_(r.shape,e);return t.runWebGLProgram(n,[r],r.dtype)}function g2(r,e,t,n){let o=e,s=r.shape.length,a=y.parseAxisParam(o,r.shape),i=a,l=S.getAxesPermutation(i,s),u=l!=null,c=r;u&&(c=xl(r,l,n),i=S.getInnerMostAxes(i.length,s)),S.assertAxesAreInnerMostDims("sum",i,s);let[p,m]=S.computeOutAndReduceShapes(c.shape,i),f=p;t&&(f=S.expandShapeToKeepDim(p,a));let d=y.sizeFromShape(m),g=y.sizeFromShape(r.shape)/d,x=pe({inputs:{x:c},attrs:{shape:[g,d]},backend:n}),w=fu(r.dtype),b=Nn(x,w,"sum",n),k=pe({inputs:{x:b},attrs:{shape:f},backend:n});return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(b),u&&n.disposeIntermediateTensorInfo(c),k}function If(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{axis:s,keepDims:a}=n;return g2(o,s,a,t)}var x2={kernelName:Do,backendName:"webgl",kernelFunc:If};function Lt(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{perm:s}=n,a=t,i=o.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=o.shape[s[c]];let u;if(a.shouldExecuteOnCPU([o])){let p=a.texData.get(o.dataId).values,m=kp(p,o.shape,o.dtype,s,l);u=a.makeTensorInfo(l,o.dtype);let f=a.texData.get(u.dataId);f.values=m}else u=xl(o,s,a);return u}var y2={kernelName:Po,backendName:"webgl",kernelFunc:Lt};var H_=1e3;function Qu({a:r,b:e,transposeA:t,transposeB:n,backend:o,bias:s=null,preluActivationWeights:a=null,leakyreluAlpha:i=0,activation:l=null}){let u=r.shape.length,c=e.shape.length,p=t?r.shape[u-2]:r.shape[u-1],m=n?e.shape[c-1]:e.shape[c-2],f=t?r.shape[u-1]:r.shape[u-2],d=n?e.shape[c-2]:e.shape[c-1],h=r.shape.slice(0,-2),g=e.shape.slice(0,-2),x=y.sizeFromShape(h),w=y.sizeFromShape(g),b=x===w||x===1||w===1;y.assert(u>=2&&c>=2&&b,()=>`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 (${h}) and (${g}).`);let _=(x>w?r.shape.slice(0,-2):e.shape.slice(0,-2)).concat([f,d]);y.assert(p===m,()=>`Error in matMul: inner shapes (${p}) and (${m}) of Tensors with shapes ${r.shape} and ${e.shape} and transposeA=${t} and transposeB=${n} must match.`);let A=t?[x,p,f]:[x,f,p],N=n?[w,d,m]:[w,m,d],$=pe({inputs:{x:r},backend:o,attrs:{shape:A}}),F=pe({inputs:{x:e},backend:o,attrs:{shape:N}}),M=[$,F],V=Math.max(x,w),W=t?$.shape[1]:$.shape[2],U=s!=null,H=a!=null,q=l==="leakyrelu",X=l!=null?gl(l,!0):null,ne=U||H||q||X!=null,Y;if((f===1||d===1)&&W>H_&&ne===!1){let J=$,ie=F;t&&(J=Lt({inputs:{x:$},backend:o,attrs:{perm:[0,2,1]}}),M.push(J)),n&&(ie=Lt({inputs:{x:F},backend:o,attrs:{perm:[0,2,1]}}),M.push(ie));let ue=d!==1,ae=d===1,fe=J;ue&&(fe=pe({inputs:{x:J},backend:o,attrs:{shape:[V,W,1]}}),M.push(fe));let de=d===1?2:1,xe=ie;ae&&(xe=pe({inputs:{x:ie},backend:o,attrs:{shape:[V,1,W]}}),M.push(xe));let we=G_({inputs:{a:fe,b:xe},backend:o});Y=If({inputs:{x:we},backend:o,attrs:{axis:de,keepDims:!0}}),M.push(we)}else{let J=dr(r.dtype,e.dtype),ie=new Cf(A,N,[V,f,d],t,n,U,X,H,q),ue=[$,F];if(s!=null&&ue.push(s),H&&ue.push(a),q){let ae=o.makeTensorInfo([],"float32",y.createScalarValue(i,"float32"));ue.push(ae),M.push(ae)}Y=o.runWebGLProgram(ie,ue,J)}let re=pe({inputs:{x:Y},backend:o,attrs:{shape:_}});M.push(Y);for(let J of M)o.disposeIntermediateTensorInfo(J);return re}function a8(r){let{inputs:e,backend:t,attrs:n}=r,{a:o,b:s,bias:a,preluActivationWeights:i}=e,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=n;return Qu({a:o,b:s,transposeA:l,transposeB:u,backend:t,bias:a,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var b2={kernelName:ws,backendName:"webgl",kernelFunc:a8};var w2="return abs(x);";function l8(r){let{inputs:e,backend:t}=r,{x:n}=e;if(t.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=t.texData.get(n.dataId),a=Vg(s.values);return t.makeTensorInfo(n.shape,n.dtype,a)}let o;return j().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new Os(n.shape,w2):o=new ln(n.shape,w2),t.runWebGLProgram(o,[n],n.dtype)}var k2={kernelName:as,backendName:"webgl",kernelFunc:l8};var u8=gr+`
+    `}};function xl(r,e,t){let o=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new L_(r.shape,e):new M_(r.shape,e);return t.runWebGLProgram(o,[r],r.dtype)}function qE(r,e,t,o){let n=e,s=r.shape.length,a=y.parseAxisParam(n,r.shape),i=a,l=N.getAxesPermutation(i,s),u=l!=null,c=r;u&&(c=xl(r,l,o),i=N.getInnerMostAxes(i.length,s)),N.assertAxesAreInnerMostDims("sum",i,s);let[p,m]=N.computeOutAndReduceShapes(c.shape,i),f=p;t&&(f=N.expandShapeToKeepDim(p,a));let d=y.sizeFromShape(m),g=y.sizeFromShape(r.shape)/d,x=pe({inputs:{x:c},attrs:{shape:[g,d]},backend:o}),b=fu(r.dtype),w=No(x,b,"sum",o),k=pe({inputs:{x:w},attrs:{shape:f},backend:o});return o.disposeIntermediateTensorInfo(x),o.disposeIntermediateTensorInfo(w),u&&o.disposeIntermediateTensorInfo(c),k}function Cf(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o;return qE(n,s,a,t)}var KE={kernelName:Dn,backendName:"webgl",kernelFunc:Cf};function Mt(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{perm:s}=o,a=t,i=n.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=n.shape[s[c]];let u;if(a.shouldExecuteOnCPU([n])){let p=a.texData.get(n.dataId).values,m=wp(p,n.shape,n.dtype,s,l);u=a.makeTensorInfo(l,n.dtype);let f=a.texData.get(u.dataId);f.values=m}else u=xl(n,s,a);return u}var XE={kernelName:Pn,backendName:"webgl",kernelFunc:Mt};var z_=1e3;function Ju({a:r,b:e,transposeA:t,transposeB:o,backend:n,bias:s=null,preluActivationWeights:a=null,leakyreluAlpha:i=0,activation:l=null}){let u=r.shape.length,c=e.shape.length,p=t?r.shape[u-2]:r.shape[u-1],m=o?e.shape[c-1]:e.shape[c-2],f=t?r.shape[u-1]:r.shape[u-2],d=o?e.shape[c-2]:e.shape[c-1],h=r.shape.slice(0,-2),g=e.shape.slice(0,-2),x=y.sizeFromShape(h),b=y.sizeFromShape(g),w=x===b||x===1||b===1;y.assert(u>=2&&c>=2&&w,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${h}) and (${g}).`);let _=(x>b?r.shape.slice(0,-2):e.shape.slice(0,-2)).concat([f,d]);y.assert(p===m,()=>`Error in matMul: inner shapes (${p}) and (${m}) of Tensors with shapes ${r.shape} and ${e.shape} and transposeA=${t} and transposeB=${o} must match.`);let D=t?[x,p,f]:[x,f,p],T=o?[b,d,m]:[b,m,d],R=pe({inputs:{x:r},backend:n,attrs:{shape:D}}),O=pe({inputs:{x:e},backend:n,attrs:{shape:T}}),M=[R,O],G=Math.max(x,b),j=t?R.shape[1]:R.shape[2],U=s!=null,H=a!=null,q=l==="leakyrelu",X=l!=null?gl(l,!0):null,oe=U||H||q||X!=null,Y;if((f===1||d===1)&&j>z_&&oe===!1){let J=R,ie=O;t&&(J=Mt({inputs:{x:R},backend:n,attrs:{perm:[0,2,1]}}),M.push(J)),o&&(ie=Mt({inputs:{x:O},backend:n,attrs:{perm:[0,2,1]}}),M.push(ie));let ue=d!==1,ae=d===1,fe=J;ue&&(fe=pe({inputs:{x:J},backend:n,attrs:{shape:[G,j,1]}}),M.push(fe));let de=d===1?2:1,xe=ie;ae&&(xe=pe({inputs:{x:ie},backend:n,attrs:{shape:[G,1,j]}}),M.push(xe));let we=O_({inputs:{a:fe,b:xe},backend:n});Y=Cf({inputs:{x:we},backend:n,attrs:{axis:de,keepDims:!0}}),M.push(we)}else{let J=dr(r.dtype,e.dtype),ie=new vf(D,T,[G,f,d],t,o,U,X,H,q),ue=[R,O];if(s!=null&&ue.push(s),H&&ue.push(a),q){let ae=n.makeTensorInfo([],"float32",y.createScalarValue(i,"float32"));ue.push(ae),M.push(ae)}Y=n.runWebGLProgram(ie,ue,J)}let re=pe({inputs:{x:Y},backend:n,attrs:{shape:_}});M.push(Y);for(let J of M)n.disposeIntermediateTensorInfo(J);return re}function $5(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s,bias:a,preluActivationWeights:i}=e,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=o;return Ju({a:n,b:s,transposeA:l,transposeB:u,backend:t,bias:a,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var YE={kernelName:ws,backendName:"webgl",kernelFunc:$5};var ZE="return abs(x);";function R5(r){let{inputs:e,backend:t}=r,{x:o}=e;if(t.shouldExecuteOnCPU([o])&&o.dtype!=="complex64"){let s=t.texData.get(o.dataId),a=Lg(s.values);return t.makeTensorInfo(o.shape,o.dtype,a)}let n;return W().getBool("WEBGL_PACK_UNARY_OPERATIONS")?n=new Os(o.shape,ZE):n=new ao(o.shape,ZE),t.runWebGLProgram(n,[o],o.dtype)}var JE={kernelName:as,backendName:"webgl",kernelFunc:R5};var F5=gr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return acos(x);
-`,c8=ke({opSnippet:u8}),_2={kernelName:qs,backendName:"webgl",kernelFunc:c8};var p8=gr+`
+`,O5=ke({opSnippet:F5}),QE={kernelName:qs,backendName:"webgl",kernelFunc:O5};var P5=gr+`
   if (x < 1.0) return NAN;
-return log(x + sqrt(x * x - 1.0));`,m8=ke({opSnippet:p8}),v2={kernelName:Ks,backendName:"webgl",kernelFunc:m8};var C2="return a + b;",f8=ot({opSnippet:C2,packedOpSnippet:C2,supportsComplex:!0,cpuKernelImpl:_E}),I2={kernelName:wn,backendName:"webgl",kernelFunc:f8};var q_=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let n=[];this.variableNames.forEach(s=>{n.push(`float v${s} = get${s}AtOutCoords();`)});let o=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
+return log(x + sqrt(x * x - 1.0));`,M5=ke({opSnippet:P5}),e2={kernelName:Ks,backendName:"webgl",kernelFunc:M5};var t2="return a + b;",L5=nt({opSnippet:t2,packedOpSnippet:t2,supportsComplex:!0,cpuKernelImpl:QA}),r2={kernelName:wo,backendName:"webgl",kernelFunc:L5};var B_=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let o=[];this.variableNames.forEach(s=>{o.push(`float v${s} = get${s}AtOutCoords();`)});let n=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
       void main() {
-        ${n.join(`
+        ${o.join(`
         `)}
 
-        float result = ${o};
+        float result = ${n};
         setOutput(result);
       }
-    `}};var K_=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let n=[];this.variableNames.forEach(s=>{n.push(`vec4 v${s} = get${s}AtOutCoords();`)});let o=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
+    `}};var V_=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((s,a)=>`T${a}`);let o=[];this.variableNames.forEach(s=>{o.push(`vec4 v${s} = get${s}AtOutCoords();`)});let n=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
       void main() {
-        ${n.join(`
+        ${o.join(`
         `)}
 
-        vec4 result = ${o};
+        vec4 result = ${n};
         setOutput(result);
       }
-    `}};function qg(r){let{inputs:e,backend:t}=r,n=e;if(n.length===1)return Ut({inputs:{x:n[0]},backend:t});if(n.length>j().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(n.length/2),u=qg({inputs:n.slice(0,l),backend:t}),c=qg({inputs:n.slice(l),backend:t});return qg({inputs:[u,c],backend:t})}let o=n.map(l=>l.dtype).reduce((l,u)=>dr(l,u)),s=n.map(l=>l.shape),i=j().getBool("WEBGL_PACK")?new K_(n[0].shape,s):new q_(n[0].shape,s);return t.runWebGLProgram(i,n,o)}var N2={kernelName:Hn,backendName:"webgl",kernelFunc:qg};function d8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{axis:s,keepDims:a}=n,i=o.shape.length,l=y.parseAxisParam(s,o.shape),u=l,c=S.getAxesPermutation(u,i),p=o;c!=null&&(p=Lt({inputs:{x:o},backend:t,attrs:{perm:c}}),u=S.getInnerMostAxes(u.length,i)),S.assertAxesAreInnerMostDims("all",u,i);let[m,f]=S.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=Nn(h,h.dtype,"all",t),x;if(a){let w=S.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:w}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var S2={kernelName:Ml,backendName:"webgl",kernelFunc:d8};function h8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{axis:s,keepDims:a}=n,i=o.shape.length,l=y.parseAxisParam(s,o.shape),u=l,c=S.getAxesPermutation(u,i),p=o;c!=null&&(p=Lt({inputs:{x:o},backend:t,attrs:{perm:c}}),u=S.getInnerMostAxes(u.length,i)),S.assertAxesAreInnerMostDims("any",u,i);let[m,f]=S.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=Nn(h,h.dtype,"any",t),x;if(a){let w=S.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:w}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var T2={kernelName:Ll,backendName:"webgl",kernelFunc:h8};var X_=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:o,batchSize:s,outSize:a}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[s,a];let i=t==="max"?">":"<",l=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
+    `}};function jg(r){let{inputs:e,backend:t}=r,o=e;if(o.length===1)return jt({inputs:{x:o[0]},backend:t});if(o.length>W().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(o.length/2),u=jg({inputs:o.slice(0,l),backend:t}),c=jg({inputs:o.slice(l),backend:t});return jg({inputs:[u,c],backend:t})}let n=o.map(l=>l.dtype).reduce((l,u)=>dr(l,u)),s=o.map(l=>l.shape),i=W().getBool("WEBGL_PACK")?new V_(o[0].shape,s):new B_(o[0].shape,s);return t.runWebGLProgram(i,o,n)}var o2={kernelName:Ho,backendName:"webgl",kernelFunc:jg};function z5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=n;c!=null&&(p=Mt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=N.getInnerMostAxes(u.length,i)),N.assertAxesAreInnerMostDims("all",u,i);let[m,f]=N.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=No(h,h.dtype,"all",t),x;if(a){let b=N.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var n2={kernelName:Ml,backendName:"webgl",kernelFunc:z5};function B5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=n;c!=null&&(p=Mt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=N.getInnerMostAxes(u.length,i)),N.assertAxesAreInnerMostDims("any",u,i);let[m,f]=N.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=No(h,h.dtype,"any",t),x;if(a){let b=N.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var s2={kernelName:Ll,backendName:"webgl",kernelFunc:B5};var G_=class{constructor(e,t,o){this.variableNames=["A"];let{windowSize:n,batchSize:s,outSize:a}=e;o||this.variableNames.push("bestIndicesA"),this.outputShape=[s,a];let i=t==="max"?">":"<",l=o?"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 * ${o};
+        int inOffset = outIdx * ${n};
 
         int bestIndex = inOffset;
         float bestValue = getA(batch, bestIndex);
 
-        for (int i = 0; i < ${o}; i++) {
+        for (int i = 0; i < ${n}; i++) {
           int inIdx = ${l};
           float candidate = getA(batch, inIdx);
           if (candidate ${i} bestValue) {
@@ -1258,14 +1258,14 @@ return log(x + sqrt(x * x - 1.0));`,m8=ke({opSnippet:p8}),v2={kernelName:Ks,back
         }
         setOutput(float(bestIndex));
       }
-    `}};var Y_=class{constructor(e,t,n,o){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,y.assert(e.length>2,()=>`Packed arg${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),o||this.variableNames.push("bestIndicesA");let i=this.outputShape,l=i.length,u=Le(l),c=jt("coords",l),p,m;if(a===1){m=l+1;let $=Le(m);p=`
-        ${$} sourceLocR = ${$}(${c.join()}, 0);
+    `}};var W_=class{constructor(e,t,o,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,y.assert(e.length>2,()=>`Packed arg${o.charAt(0).toUpperCase()+o.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),n||this.variableNames.push("bestIndicesA");let i=this.outputShape,l=i.length,u=Le(l),c=Wt("coords",l),p,m;if(a===1){m=l+1;let R=Le(m);p=`
+        ${R} sourceLocR = ${R}(${c.join()}, 0);
         ++${c[l-1]};
-        ${$} sourceLocG = ${$}(${c.join()}, 0);
+        ${R} sourceLocG = ${R}(${c.join()}, 0);
         ++${c[l-2]};
-        ${$} sourceLocA = ${$}(${c.join()}, 0);
+        ${R} sourceLocA = ${R}(${c.join()}, 0);
         --${c[l-1]};
-        ${$} sourceLocB = ${$}(${c.join()}, 0);
+        ${R} sourceLocB = ${R}(${c.join()}, 0);
         --${c[l-2]};`}else m=l,p=`
         ${u} sourceLocR = coords;
         ++${c[l-1]};
@@ -1274,15 +1274,15 @@ return log(x + sqrt(x * x - 1.0));`,m8=ke({opSnippet:p8}),v2={kernelName:Ks,back
         ${u} sourceLocA = coords;
         --${c[l-1]};
         ${u} sourceLocB = coords;
-        --${c[l-2]};`;let f=["x","y","z","w","u","v"].slice(0,m),d="."+f[m-1],h=f.map($=>"int "+$),g=jt("sourceLocR",m-1).concat("inIdx.r"),x=jt("sourceLocG",m-1).concat("inIdx.g"),w=jt("sourceLocB",m-1).concat("inIdx.b"),b=jt("sourceLocA",m-1).concat("inIdx.a"),k=n==="max"?"greaterThan":"lessThan",_=o?"":`
+        --${c[l-2]};`;let f=["x","y","z","w","u","v"].slice(0,m),d="."+f[m-1],h=f.map(R=>"int "+R),g=Wt("sourceLocR",m-1).concat("inIdx.r"),x=Wt("sourceLocG",m-1).concat("inIdx.g"),b=Wt("sourceLocB",m-1).concat("inIdx.b"),w=Wt("sourceLocA",m-1).concat("inIdx.a"),k=o==="max"?"greaterThan":"lessThan",_=n?"":`
           inIdx = round(vec4(getBestIndicesAChannel(${g.join()}),
                              getBestIndicesAChannel(${x.join()}),
-                             getBestIndicesAChannel(${w.join()}),
-                             getBestIndicesAChannel(${b.join()})));`,A=`vec4(
+                             getBestIndicesAChannel(${b.join()}),
+                             getBestIndicesAChannel(${w.join()})));`,D=`vec4(
             getAChannel(${g.join()}),
             hasNextCol ? getAChannel(${x.join()}) : 0.,
-            hasNextRow ? getAChannel(${w.join()}) : 0.,
-            hasNextRow && hasNextCol ? getAChannel(${b.join()}) : 0.)`,N=o?"":`
+            hasNextRow ? getAChannel(${b.join()}) : 0.,
+            hasNextRow && hasNextCol ? getAChannel(${w.join()}) : 0.)`,T=n?"":`
       float getBestIndicesAChannel(${h.join()}) {
         return getChannel(getBestIndicesA(${f.join()}),
                                           vec2(${f.slice(-2).join()}));
@@ -1291,7 +1291,7 @@ return log(x + sqrt(x * x - 1.0));`,m8=ke({opSnippet:p8}),v2={kernelName:Ks,back
         return getChannel(getA(${f.join()}),
                                vec2(${f.slice(-2).join()}));
       }
-      ${N}
+      ${T}
       void main() {
         ${u} coords = getOutputCoords();
         bool hasNextCol = ${c[l-1]} < ${i[l-1]-1};
@@ -1301,12 +1301,12 @@ return log(x + sqrt(x * x - 1.0));`,m8=ke({opSnippet:p8}),v2={kernelName:Ks,back
           sourceLocB${d}, sourceLocA${d}) * ${t};
         ivec4 inIdx = srcIdx;
         vec4 bestIndex = vec4(inIdx);
-        vec4 bestValue = ${A};
+        vec4 bestValue = ${D};
 
         for (int i = 0; i < ${t}; i++) {
           inIdx = srcIdx;
           ${_}
-          vec4 candidate = ${A};
+          vec4 candidate = ${D};
           bvec4 nan = isnan(candidate);
           bvec4 replace = bvec4(
             vec4(${k}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
@@ -1320,23 +1320,23 @@ return log(x + sqrt(x * x - 1.0));`,m8=ke({opSnippet:p8}),v2={kernelName:Ks,back
         }
         setOutput(bestIndex);
       }
-    `}};function A2(r,e,t,n=null){let o=e.shape[0],s=e.shape[1];n!=null&&(o=n.shape[0],s=n.shape[1]);let a=S.computeOptimalWindowSize(s),i={windowSize:a,inSize:s,batchSize:o,outSize:Math.ceil(s/a)},l=new X_(i,t,n==null),u=[e];n!=null&&u.push(n);let c=r.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let p=A2(r,e,t,c);return r.disposeIntermediateTensorInfo(c),p}function E2(r,e,t,n=null){let o=n!=null?n.shape:e.shape,s=o[o.length-1],a=S.computeOptimalWindowSize(s),i=new Y_(o,a,t,n==null),l=n==null?[e]:[e,n],u=r.runWebGLProgram(i,l,"int32");if(u.shape.length===e.shape.length){let c=E2(r,e,t,u);return r.disposeIntermediateTensorInfo(u),c}return u}function Kg(r,e,t,n){let o=[t];if(S.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),o,e.shape.length),!j().getBool("WEBGL_PACK_REDUCE")||e.shape.length<=2){let s=[],[a,i]=S.computeOutAndReduceShapes(e.shape,o),l=y.sizeFromShape(i),u=pe({inputs:{x:e},backend:r,attrs:{shape:[-1,l]}});s.push(u);let c=A2(r,u,n);s.push(c);let p=pe({inputs:{x:c},backend:r,attrs:{shape:a}});return s.forEach(m=>r.disposeIntermediateTensorInfo(m)),p}return E2(r,e,n)}function g8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{axis:s}=n,a=y.parseAxisParam(s,o.shape),i=S.getAxesPermutation(a,o.shape.length),l=o,u=[];i!=null&&(l=Lt({inputs:{x:o},backend:t,attrs:{perm:i}}),u.push(l),a=S.getInnerMostAxes(a.length,l.shape.length)),S.assertAxesAreInnerMostDims("argMax",[a[0]],l.shape.length);let c=Kg(t,l,a[0],"max");return u.forEach(p=>t.disposeIntermediateTensorInfo(p)),c}var D2={kernelName:qn,backendName:"webgl",kernelFunc:g8};function x8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{axis:s}=n,a=y.parseAxisParam(s,o.shape),i=S.getAxesPermutation(a,o.shape.length),l=o,u=[];i!=null&&(l=Lt({inputs:{x:o},backend:t,attrs:{perm:i}}),u.push(l),a=S.getInnerMostAxes(a.length,l.shape.length)),S.assertAxesAreInnerMostDims("argMin",[a[0]],l.shape.length);let c=Kg(t,l,a[0],"min");return u.forEach(p=>t.disposeIntermediateTensorInfo(p)),c}var $2={kernelName:ea,backendName:"webgl",kernelFunc:x8};var y8=gr+`
+    `}};function i2(r,e,t,o=null){let n=e.shape[0],s=e.shape[1];o!=null&&(n=o.shape[0],s=o.shape[1]);let a=N.computeOptimalWindowSize(s),i={windowSize:a,inSize:s,batchSize:n,outSize:Math.ceil(s/a)},l=new G_(i,t,o==null),u=[e];o!=null&&u.push(o);let c=r.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let p=i2(r,e,t,c);return r.disposeIntermediateTensorInfo(c),p}function a2(r,e,t,o=null){let n=o!=null?o.shape:e.shape,s=n[n.length-1],a=N.computeOptimalWindowSize(s),i=new W_(n,a,t,o==null),l=o==null?[e]:[e,o],u=r.runWebGLProgram(i,l,"int32");if(u.shape.length===e.shape.length){let c=a2(r,e,t,u);return r.disposeIntermediateTensorInfo(u),c}return u}function Ug(r,e,t,o){let n=[t];if(N.assertAxesAreInnerMostDims("arg"+o.charAt(0).toUpperCase()+o.slice(1),n,e.shape.length),!W().getBool("WEBGL_PACK_REDUCE")||e.shape.length<=2){let s=[],[a,i]=N.computeOutAndReduceShapes(e.shape,n),l=y.sizeFromShape(i),u=pe({inputs:{x:e},backend:r,attrs:{shape:[-1,l]}});s.push(u);let c=i2(r,u,o);s.push(c);let p=pe({inputs:{x:c},backend:r,attrs:{shape:a}});return s.forEach(m=>r.disposeIntermediateTensorInfo(m)),p}return a2(r,e,o)}function V5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=N.getAxesPermutation(a,n.shape.length),l=n,u=[];i!=null&&(l=Mt({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(l),a=N.getInnerMostAxes(a.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMax",[a[0]],l.shape.length);let c=Ug(t,l,a[0],"max");return u.forEach(p=>t.disposeIntermediateTensorInfo(p)),c}var l2={kernelName:qo,backendName:"webgl",kernelFunc:V5};function G5(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s}=o,a=y.parseAxisParam(s,n.shape),i=N.getAxesPermutation(a,n.shape.length),l=n,u=[];i!=null&&(l=Mt({inputs:{x:n},backend:t,attrs:{perm:i}}),u.push(l),a=N.getInnerMostAxes(a.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMin",[a[0]],l.shape.length);let c=Ug(t,l,a[0],"min");return u.forEach(p=>t.disposeIntermediateTensorInfo(p)),c}var u2={kernelName:ea,backendName:"webgl",kernelFunc:G5};var W5=gr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return asin(x);
-`,b8=ke({opSnippet:y8}),R2={kernelName:Xs,backendName:"webgl",kernelFunc:b8};var w8=gr+"return log(x + sqrt(x * x + 1.0));",k8=ke({opSnippet:w8}),F2={kernelName:Ys,backendName:"webgl",kernelFunc:k8};var _8=gr+`
+`,j5=ke({opSnippet:W5}),c2={kernelName:Xs,backendName:"webgl",kernelFunc:j5};var U5=gr+"return log(x + sqrt(x * x + 1.0));",H5=ke({opSnippet:U5}),p2={kernelName:Ys,backendName:"webgl",kernelFunc:H5};var q5=gr+`
   return atan(x);
-`,v8=ke({opSnippet:_8}),O2={kernelName:Zs,backendName:"webgl",kernelFunc:v8};var C8=c2+`
+`,K5=ke({opSnippet:q5}),m2={kernelName:Zs,backendName:"webgl",kernelFunc:K5};var X5=VE+`
   return atan(a, b);
-`,I8=`
+`,Y5=`
   vec4 result = atan(a, b);
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+p2+`
+  `+GE+`
   return result;
-`,N8=ot({opSnippet:C8,packedOpSnippet:I8}),P2={kernelName:Qs,backendName:"webgl",kernelFunc:N8};var S8=gr+`
+`,Z5=nt({opSnippet:X5,packedOpSnippet:Y5}),f2={kernelName:Qs,backendName:"webgl",kernelFunc:Z5};var J5=gr+`
   if ((x < -1.0) || (x > 1.0)) return NAN;
-return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelName:Js,backendName:"webgl",kernelFunc:T8};var Vi=class{constructor(e,t,n,o=!1,s=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,i=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,p=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.top,d=e.padInfo.left;this.outputShape=e.outShape;let h=t==="avg",g=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,x=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,w="0.0";if(h||(w="-1.0 / 1e-20"),n){let $=">=";this.userCode=`
+return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,Q5=ke({opSnippet:J5}),d2={kernelName:Js,backendName:"webgl",kernelFunc:Q5};var Vi=class{constructor(e,t,o,n=!1,s=!1){if(this.variableNames=["x"],t==="avg"&&o)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,i=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,p=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.top,d=e.padInfo.left;this.outputShape=e.outShape;let h=t==="avg",g=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,x=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,b="0.0";if(h||(b="-1.0 / 1e-20"),o){let R=">=";this.userCode=`
         const ivec2 strides = ivec2(${i}, ${l});
         const ivec2 pads = ivec2(${f}, ${d});
 
@@ -1378,25 +1378,25 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
               // use the current value.
               float currMinMaxValue = mix(
                   value, minMaxValue, minMaxValueFound);
-              if (value ${$} currMinMaxValue) {
+              if (value ${R} currMinMaxValue) {
                 minMaxValue = value;
                 minMaxValueFound = 1.0;
-                minMaxPosition = ${o?s?g:x:`wR * ${m} + wC`};
+                minMaxPosition = ${n?s?g:x:`wR * ${m} + wC`};
               }
             }
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let b="max",k=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(k="avgValue / count");let _=Math.floor(a/4)*4,A=a%4,N=`
+      `;return}let w="max",k=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(k="avgValue / count");let _=Math.floor(a/4)*4,D=a%4,T=`
       if (${h}) {
         avgValue += dot(values, ones);
       } else {
-        minMaxValue = ${b}(values, minMaxValue);
+        minMaxValue = ${w}(values, minMaxValue);
       }
     `;this.userCode=`
       const ivec2 strides = ivec2(${i}, ${l});
       const ivec2 pads = ivec2(${f}, ${d});
-      const float initializationValue = ${w};
+      const float initializationValue = ${b};
       const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
 
       float count = 0.0;
@@ -1420,7 +1420,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
         // max/min x(?, ?, d) to get y(yR, yC, d).
         // ? = to be determined
-        vec4 minMaxValue = vec4(${w});
+        vec4 minMaxValue = vec4(${b});
         float avgValue = 0.0;
         count = 0.0;
 
@@ -1442,11 +1442,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
               getValue(batch, xR, xC + 3 * ${c}, d)
             );
 
-            ${N}
+            ${T}
           }
 
           int xC = xCCorner + ${_};
-          if (${A===1}) {
+          if (${D===1}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
               initializationValue,
@@ -1454,8 +1454,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
               initializationValue
             );
 
-            ${N}
-          } else if (${A===2}) {
+            ${T}
+          } else if (${D===2}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
               getValue(batch, xR, xC + ${c}, d),
@@ -1463,8 +1463,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
               initializationValue
             );
 
-            ${N}
-          } else if (${A===3}) {
+            ${T}
+          } else if (${D===3}) {
             vec4 values = vec4(
               getValue(batch, xR, xC, d),
               getValue(batch, xR, xC + ${c}, d),
@@ -1472,15 +1472,15 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
               initializationValue
             );
 
-            ${N}
+            ${T}
           }
         }
         setOutput(${k});
       }
-    `}},ec=class{constructor(e,t,n,o=!1,s=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,i=e.strideDepth,l=e.strideHeight,u=e.strideWidth,c=e.dilationDepth,p=e.dilationHeight,m=e.dilationWidth,f=e.effectiveFilterDepth,d=e.effectiveFilterHeight,h=e.effectiveFilterWidth,g=e.padInfo.front,x=e.padInfo.top,w=e.padInfo.left;this.outputShape=e.outShape;let b=t==="avg",k="0.0";if(b||(k="-1.0 / 1e-20"),n){let M=">=";this.userCode=`
+    `}},Qu=class{constructor(e,t,o,n=!1,s=!1){if(this.variableNames=["x"],t==="avg"&&o)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,i=e.strideDepth,l=e.strideHeight,u=e.strideWidth,c=e.dilationDepth,p=e.dilationHeight,m=e.dilationWidth,f=e.effectiveFilterDepth,d=e.effectiveFilterHeight,h=e.effectiveFilterWidth,g=e.padInfo.front,x=e.padInfo.top,b=e.padInfo.left;this.outputShape=e.outShape;let w=t==="avg",k="0.0";if(w||(k="-1.0 / 1e-20"),o){let M=">=";this.userCode=`
         const ivec3 strides =
             ivec3(${i}, ${l}, ${u});
-        const ivec3 pads = ivec3(${g}, ${x}, ${w});
+        const ivec3 pads = ivec3(${g}, ${x}, ${b});
 
         void main() {
           ivec5 coords = getOutputCoords();
@@ -1531,7 +1531,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
                 if (value ${M} currMinMaxValue) {
                   minMaxValue = value;
                   minMaxValueFound = 1.0;
-                  minMaxPosition = ${o?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 * ${d} * ${h} +
+                  minMaxPosition = ${n?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 * ${d} * ${h} +
                       wR * ${h} + wC`};
                 }
               }
@@ -1539,8 +1539,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
           }
           setOutput(float(minMaxPosition));
         }
-      `;return}let _="max",A=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(A="avgValue / count");let N=Math.floor(a/4)*4,$=a%4,F=`
-      if (${b}) {
+      `;return}let _="max",D=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(D="avgValue / count");let T=Math.floor(a/4)*4,R=a%4,O=`
+      if (${w}) {
         avgValue += dot(values, ones);
       } else {
         minMaxValue = ${_}(values, minMaxValue);
@@ -1548,7 +1548,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
     `;this.userCode=`
       const ivec3 strides =
         ivec3(${i}, ${l}, ${u});
-      const ivec3 pads = ivec3(${g}, ${x}, ${w});
+      const ivec3 pads = ivec3(${g}, ${x}, ${b});
       const float initializationValue = ${k};
       const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
 
@@ -1594,7 +1594,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
               continue;
             }
 
-            for (int wC = 0; wC < ${N}; wC += 4) {
+            for (int wC = 0; wC < ${T}; wC += 4) {
               int xC = xCCorner + wC * ${m};
 
               vec4 values = vec4(
@@ -1604,11 +1604,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
                 getValue(batch, xD, xR, xC + 3 * ${m}, ch)
               );
 
-              ${F}
+              ${O}
             }
 
-            int xC = xCCorner + ${N};
-            if (${$===1}) {
+            int xC = xCCorner + ${T};
+            if (${R===1}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
                 initializationValue,
@@ -1616,8 +1616,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
                 initializationValue
               );
 
-              ${F}
-            } else if (${$===2}) {
+              ${O}
+            } else if (${R===2}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
                 getValue(batch, xD, xR, xC + ${m}, ch),
@@ -1625,8 +1625,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
                 initializationValue
               );
 
-              ${F}
-            } else if (${$===3}) {
+              ${O}
+            } else if (${R===3}) {
               vec4 values = vec4(
                 getValue(batch, xD, xR, xC, ch),
                 getValue(batch, xD, xR, xC + ${m}, ch),
@@ -1634,13 +1634,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
                 initializationValue
               );
 
-              ${F}
+              ${O}
             }
           }
-          setOutput(${A});
+          setOutput(${D});
         }
       }
-    `}};function A8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e;Rs(o,"avgPool");let{filterSize:s,strides:a,pad:i,dimRoundingMode:l}=n,u=1;y.assert(S.eitherStridesOrDilationsAreOne(a,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=S.computePool2DInfo(o.shape,s,a,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return Ut({inputs:{x:o},backend:t});let p=new Vi(c,"avg",!1);return t.runWebGLProgram(p,[o],"float32")}var L2={kernelName:Kn,backendName:"webgl",kernelFunc:A8};function E8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{filterSize:s,strides:a,pad:i,dimRoundingMode:l,dataFormat:u}=n,c=[1,1,1],p=S.computePool3DInfo(o.shape,s,a,c,i,l,u),m=new ec(p,"avg",!1);return t.runWebGLProgram(m,[o],"float32")}var z2={kernelName:ta,backendName:"webgl",kernelFunc:E8};var Z_=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,o=e.strideHeight,s=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=l-1-e.padInfo.top,p=u-1-e.padInfo.left,m=1/(t*n);this.userCode=`
+    `}};function eX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e;Rs(n,"avgPool");let{filterSize:s,strides:a,pad:i,dimRoundingMode:l}=o,u=1;y.assert(N.eitherStridesOrDilationsAreOne(a,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=N.computePool2DInfo(n.shape,s,a,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return jt({inputs:{x:n},backend:t});let p=new Vi(c,"avg",!1);return t.runWebGLProgram(p,[n],"float32")}var h2={kernelName:Ko,backendName:"webgl",kernelFunc:eX};function tX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{filterSize:s,strides:a,pad:i,dimRoundingMode:l,dataFormat:u}=o,c=[1,1,1],p=N.computePool3DInfo(n.shape,s,a,c,i,l,u),m=new Qu(p,"avg",!1);return t.runWebGLProgram(m,[n],"float32")}var g2={kernelName:ta,backendName:"webgl",kernelFunc:tX};var j_=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=e.dilationHeight,i=e.dilationWidth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=l-1-e.padInfo.top,p=u-1-e.padInfo.left,m=1/(t*o);this.userCode=`
       const ivec2 pads = ivec2(${c}, ${p});
       const float avgMultiplier = float(${m});
 
@@ -1658,7 +1658,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         float dotProd = 0.0;
         for (int wR = 0; wR < ${l};
             wR += ${a}) {
-          float dyR = float(dyRCorner + wR) / ${o}.0;
+          float dyR = float(dyRCorner + wR) / ${n}.0;
 
           if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
             continue;
@@ -1682,7 +1682,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},J_=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,o=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,p=e.effectiveFilterDepth,m=e.effectiveFilterHeight,f=e.effectiveFilterWidth,d=p-1-e.padInfo.front,h=m-1-e.padInfo.top,g=f-1-e.padInfo.left,x=1/(t*n*o);this.userCode=`
+    `}},U_=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,o=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,p=e.effectiveFilterDepth,m=e.effectiveFilterHeight,f=e.effectiveFilterWidth,d=p-1-e.padInfo.front,h=m-1-e.padInfo.top,g=f-1-e.padInfo.left,x=1/(t*o*n);this.userCode=`
       const ivec3 pads = ivec3(${d}, ${h}, ${g});
       const float avgMultiplier = float(${x});
 
@@ -1738,7 +1738,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function D8(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,input:s}=e,a=s,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=n,p=[1,1,1],m=S.computePool3DInfo(a.shape,i,l,p,u,c),f=new J_(m);return t.runWebGLProgram(f,[o],a.dtype)}var B2={kernelName:Bl,backendName:"webgl",kernelFunc:D8};function $8(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,input:s}=e,a=s;Rs([o,s],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=n,c=S.computePool2DInfo(a.shape,i,l,1,u),p=new Z_(c);return t.runWebGLProgram(p,[o],a.dtype)}var V2={kernelName:zl,backendName:"webgl",kernelFunc:$8};function R8(r){let{inputs:e,backend:t,attrs:n}=r,{a:o,b:s}=e,{transposeA:a,transposeB:i}=n;return Qu({a:o,b:s,transposeA:a,transposeB:i,backend:t})}var G2={kernelName:Xn,backendName:"webgl",kernelFunc:R8};var Q_=class{constructor(e,t,n,o,s,a){this.outputShape=[],this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(e,t),S.assertAndGetBroadcastShape(e,n);let i="0.0";o!=null&&(S.assertAndGetBroadcastShape(e,o),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let l="1.0";s!=null&&(S.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),l="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};function rX(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=o,p=[1,1,1],m=N.computePool3DInfo(a.shape,i,l,p,u,c),f=new U_(m);return t.runWebGLProgram(f,[n],a.dtype)}var x2={kernelName:Bl,backendName:"webgl",kernelFunc:rX};function oX(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s;Rs([n,s],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=o,c=N.computePool2DInfo(a.shape,i,l,1,u),p=new j_(c);return t.runWebGLProgram(p,[n],a.dtype)}var y2={kernelName:zl,backendName:"webgl",kernelFunc:oX};function nX(r){let{inputs:e,backend:t,attrs:o}=r,{a:n,b:s}=e,{transposeA:a,transposeB:i}=o;return Ju({a:n,b:s,transposeA:a,transposeB:i,backend:t})}var b2={kernelName:Xo,backendName:"webgl",kernelFunc:nX};var H_=class{constructor(e,t,o,n,s,a){this.outputShape=[],this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,o);let i="0.0";n!=null&&(N.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let l="1.0";s!=null&&(N.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),l="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         float x = getXAtOutCoords();
         float mean = getMeanAtOutCoords();
@@ -1748,7 +1748,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         float inv = scale * inversesqrt(variance + float(${a}));
         setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
       }
-    `}};var ev=class{constructor(e,t,n,o,s,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(e,t),S.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";o!=null&&(S.assertAndGetBroadcastShape(e,o),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let l="vec4(1.0)";s!=null&&(S.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),l="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};var q_=class{constructor(e,t,o,n,s,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,o);let i="vec4(0.0)";n!=null&&(N.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let l="vec4(1.0)";s!=null&&(N.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),l="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         vec4 offset = ${i};
         vec4 scale = ${l};
@@ -1761,36 +1761,36 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
         setOutput((x - mean) * inv + offset);
       }
-    `}};var F8=({inputs:r,backend:e,attrs:t})=>{let{x:n,mean:o,variance:s,offset:a,scale:i}=r;y.assert(o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),y.assert(a==null||o.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),y.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=t;l==null&&(l=.001);let u=[n,o,s],c=null;a!=null&&(c=a.shape,u.push(a));let p=null;i!=null&&(p=i.shape,u.push(i));let m=j().getBool("WEBGL_PACK_NORMALIZATION")?new ev(n.shape,o.shape,s.shape,c,p,l):new Q_(n.shape,o.shape,s.shape,c,p,l);return e.runWebGLProgram(m,u,u[0].dtype)},W2={kernelName:io,backendName:"webgl",kernelFunc:F8};var tv=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=Le(this.rank),n=`uniform int start[${this.rank}];`,o=O8(this.rank),s,a=e.map((i,l)=>`sourceLoc.${rv[l]} = start[${l}] + coords.${rv[l]};`);s=`
+    `}};var sX=({inputs:r,backend:e,attrs:t})=>{let{x:o,mean:n,variance:s,offset:a,scale:i}=r;y.assert(n.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),y.assert(a==null||n.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),y.assert(i==null||n.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=t;l==null&&(l=.001);let u=[o,n,s],c=null;a!=null&&(c=a.shape,u.push(a));let p=null;i!=null&&(p=i.shape,u.push(i));let m=W().getBool("WEBGL_PACK_NORMALIZATION")?new q_(o.shape,n.shape,s.shape,c,p,l):new H_(o.shape,n.shape,s.shape,c,p,l);return e.runWebGLProgram(m,u,u[0].dtype)},w2={kernelName:an,backendName:"webgl",kernelFunc:sX};var K_=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=Le(this.rank),o=`uniform int start[${this.rank}];`,n=iX(this.rank),s,a=e.map((i,l)=>`sourceLoc.${X_[l]} = start[${l}] + coords.${X_[l]};`);s=`
         ${t} sourceLoc;
         ${t} coords = getOutputCoords();
         ${a.join(`
 `)}
       `,this.userCode=`
-      ${n}
+      ${o}
       void main() {
         ${s}
-        setOutput(getSource(${o}));
+        setOutput(getSource(${n}));
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${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)}}},rv=["x","y","z","w","u","v"];function O8(r){if(r===1)return"sourceLoc";if(r<=6)return rv.slice(0,r).map(e=>"sourceLoc."+e).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}var nv=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=Le(this.rank),n=jt("coords",this.rank),o=jt("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${o.slice(-2).join()})`,a=`getChannel(getSource(${o.join()}), ${s})`,i=`
+    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,o)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(o,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}},X_=["x","y","z","w","u","v"];function iX(r){if(r===1)return"sourceLoc";if(r<=6)return X_.slice(0,r).map(e=>"sourceLoc."+e).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}var Y_=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length;let t=Le(this.rank),o=Wt("coords",this.rank),n=Wt("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${n.slice(-2).join()})`,a=`getChannel(getSource(${n.join()}), ${s})`,i=`
       result.x = ${a};
-      if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
-        ++${o[this.rank-1]};
+      if (++${o[this.rank-1]} < ${e[this.rank-1]}) {
+        ++${n[this.rank-1]};
         result.y = ${a};
-        --${o[this.rank-1]};
+        --${n[this.rank-1]};
       }
     `,l=this.rank===1?"":`
-      --${n[this.rank-1]};
-      if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
-        ++${o[this.rank-2]};
+      --${o[this.rank-1]};
+      if (++${o[this.rank-2]} < ${e[this.rank-2]}) {
+        ++${n[this.rank-2]};
         result.z = ${a};
-        if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
-          ++${o[this.rank-1]};
+        if (++${o[this.rank-1]} < ${e[this.rank-1]}) {
+          ++${n[this.rank-1]};
           result.w = ${a};
         }
       }
     `,u=this.rank<=4?`sourceLoc = coords +
-            ${t}(${e.map((c,p)=>`start[${p}]`).join()});`:e.map((c,p)=>`${o[p]} = ${n[p]} + start[${p}];`).join(`
+            ${t}(${e.map((c,p)=>`start[${p}]`).join()});`:e.map((c,p)=>`${n[p]} = ${o[p]} + start[${p}];`).join(`
 `);this.userCode=`
       uniform int start[${this.rank}];
       void main() {
@@ -1802,7 +1802,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         ${l}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${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 P8(r,e,t,n){let o=n.texData.get(r.dataId),s=n.makeTensorInfo(t,r.dtype),a=n.texData.get(s.dataId);Object.assign(a,o),a.refCount=1,a.shape=t,a.dtype=r.dtype;let i=sr.computeFlatOffset(e,y.computeStrides(r.shape));o.slice&&(i+=o.slice.flatOffset),a.slice={flatOffset:i,origDataId:o.slice&&o.slice.origDataId||r.dataId};let l=n.dataRefCount.get(a.slice.origDataId)||1;return n.dataRefCount.set(a.slice.origDataId,l+1),s}function Ma(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{begin:s,size:a}=n,[i,l]=sr.parseSliceParams(o,s,a);if(sr.assertParamsValid(o,i,l),y.sizeFromShape(l)===0)return t.makeTensorInfo(l,o.dtype,[]);if(t.shouldExecuteOnCPU([o])||o.dtype==="string"){let p=t.texData.get(o.dataId),m=GE(p.values,i,l,o.shape,o.dtype);return t.makeTensorInfo(l,o.dtype,m)}let{isPacked:u}=t.texData.get(o.dataId),c=sr.isSliceContinous(o.shape,i,l);if(u||!c){let p=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new nv(l):new tv(l),m=p.getCustomSetupFunc(i);return t.runWebGLProgram(p,[o],o.dtype,m)}return t.uploadToGPU(o.dataId),P8(o,i,l,t)}var j2={kernelName:gs,backendName:"webgl",kernelFunc:Ma};var M8=r=>{let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{blockShape:s,crops:a}=n;y.assert(o.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=s.reduce((w,b)=>w*b),l=S.getReshaped(o.shape,s,i),u=S.getPermuted(l.length,s.length),c=S.getReshapedPermuted(o.shape,s,i),p=S.getSliceBeginCoords(a,s.length),m=S.getSliceSize(c,a,s.length),f=[],d=pe({inputs:{x:o},backend:t,attrs:{shape:l}}),h=Lt({inputs:{x:d},backend:t,attrs:{perm:u}}),g=pe({inputs:{x:h},backend:t,attrs:{shape:c}}),x=Ma({inputs:{x:g},backend:t,attrs:{begin:p,size:m}});return f.push(d),f.push(h),f.push(g),f.forEach(w=>t.disposeIntermediateTensorInfo(w)),x},U2={kernelName:ra,backendName:"webgl",kernelFunc:M8};function L8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,weights:s}=e,{size:a}=n,i=t.readSync(o.dataId),l=t.readSync(s.dataId),u=Bg(i,l,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,u)}var H2={kernelName:Vl,backendName:"webgl",kernelFunc:L8};var z8="return float(a != b);",ov=ot({opSnippet:z8,dtype:"bool"}),q2={kernelName:yi,backendName:"webgl",kernelFunc:ov};function La(r){let{inputs:e,backend:t}=r,{input:n}=e,o=t.texData.get(n.dataId);return Ut({inputs:{x:o.complexTensorInfos.real},backend:t})}var K2={kernelName:iu,backendName:"webgl",kernelFunc:La};var B8="return float(int(x));";function X2(r,e){let t=new ln(r.shape,B8),n=e.runWebGLProgram(t,[r],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function sv(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{dtype:s}=n;if(s==="complex64"){if(o.dtype==="complex64")return Ut({inputs:{x:o},backend:t});let a=gt(o.shape),i=sv({inputs:{x:o},backend:t,attrs:{dtype:"float32"}}),l=un({inputs:{real:i,imag:a},backend:t});return a.dispose(),t.disposeIntermediateTensorInfo(i),l}if(o.dtype==="complex64"){let a=La({inputs:{input:o},backend:t}),i=sv({inputs:{x:a},backend:t,attrs:{dtype:s}});return t.disposeIntermediateTensorInfo(a),i}if(!y.hasEncodingLoss(o.dtype,s)){let a=Ut({inputs:{x:o},backend:t});return{dataId:a.dataId,shape:a.shape,dtype:s}}if(s==="int32")return X2(o,t);if(s==="bool"){let a=t.makeTensorInfo([],"bool",y.getTypedArrayFromDType("bool",1)),l=ov({inputs:{a:o,b:a},backend:t});return t.disposeIntermediateTensorInfo(a),l}throw new Error(`Error in Cast: failed to cast ${o.dtype} to ${s}`)}var Y2={kernelName:$n,backendName:"webgl",kernelFunc:sv};var Z2="return ceil(x);",V8=ke({opSnippet:Z2,packedOpSnippet:Z2,cpuKernelImpl:CE}),J2={kernelName:Yn,backendName:"webgl",kernelFunc:V8};var iv=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
+    `}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,o)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(o,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function aX(r,e,t,o){let n=o.texData.get(r.dataId),s=o.makeTensorInfo(t,r.dtype),a=o.texData.get(s.dataId);Object.assign(a,n),a.refCount=1,a.shape=t,a.dtype=r.dtype;let i=sr.computeFlatOffset(e,y.computeStrides(r.shape));n.slice&&(i+=n.slice.flatOffset),a.slice={flatOffset:i,origDataId:n.slice&&n.slice.origDataId||r.dataId};let l=o.dataRefCount.get(a.slice.origDataId)||1;return o.dataRefCount.set(a.slice.origDataId,l+1),s}function Ma(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{begin:s,size:a}=o,[i,l]=sr.parseSliceParams(n,s,a);if(sr.assertParamsValid(n,i,l),y.sizeFromShape(l)===0)return t.makeTensorInfo(l,n.dtype,[]);if(t.shouldExecuteOnCPU([n])||n.dtype==="string"){let p=t.texData.get(n.dataId),m=bE(p.values,i,l,n.shape,n.dtype);return t.makeTensorInfo(l,n.dtype,m)}let{isPacked:u}=t.texData.get(n.dataId),c=sr.isSliceContinous(n.shape,i,l);if(u||!c){let p=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Y_(l):new K_(l),m=p.getCustomSetupFunc(i);return t.runWebGLProgram(p,[n],n.dtype,m)}return t.uploadToGPU(n.dataId),aX(n,i,l,t)}var k2={kernelName:gs,backendName:"webgl",kernelFunc:Ma};var lX=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,crops:a}=o;y.assert(n.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=s.reduce((b,w)=>b*w),l=N.getReshaped(n.shape,s,i),u=N.getPermuted(l.length,s.length),c=N.getReshapedPermuted(n.shape,s,i),p=N.getSliceBeginCoords(a,s.length),m=N.getSliceSize(c,a,s.length),f=[],d=pe({inputs:{x:n},backend:t,attrs:{shape:l}}),h=Mt({inputs:{x:d},backend:t,attrs:{perm:u}}),g=pe({inputs:{x:h},backend:t,attrs:{shape:c}}),x=Ma({inputs:{x:g},backend:t,attrs:{begin:p,size:m}});return f.push(d),f.push(h),f.push(g),f.forEach(b=>t.disposeIntermediateTensorInfo(b)),x},_2={kernelName:ra,backendName:"webgl",kernelFunc:lX};function uX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a}=o,i=t.readSync(n.dataId),l=t.readSync(s.dataId),u=Mg(i,l,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,u)}var v2={kernelName:Vl,backendName:"webgl",kernelFunc:uX};var cX="return float(a != b);",Z_=nt({opSnippet:cX,dtype:"bool"}),C2={kernelName:yi,backendName:"webgl",kernelFunc:Z_};function La(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.texData.get(o.dataId);return jt({inputs:{x:n.complexTensorInfos.real},backend:t})}var I2={kernelName:iu,backendName:"webgl",kernelFunc:La};var pX="return float(int(x));";function N2(r,e){let t=new ao(r.shape,pX),o=e.runWebGLProgram(t,[r],"int32");return{dataId:o.dataId,shape:o.shape,dtype:o.dtype}}function J_(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dtype:s}=o;if(s==="complex64"){if(n.dtype==="complex64")return jt({inputs:{x:n},backend:t});let a=ht(n.shape),i=J_({inputs:{x:n},backend:t,attrs:{dtype:"float32"}}),l=lo({inputs:{real:i,imag:a},backend:t});return a.dispose(),t.disposeIntermediateTensorInfo(i),l}if(n.dtype==="complex64"){let a=La({inputs:{input:n},backend:t}),i=J_({inputs:{x:a},backend:t,attrs:{dtype:s}});return t.disposeIntermediateTensorInfo(a),i}if(!y.hasEncodingLoss(n.dtype,s)){let a=jt({inputs:{x:n},backend:t});return{dataId:a.dataId,shape:a.shape,dtype:s}}if(s==="int32")return N2(n,t);if(s==="bool"){let a=t.makeTensorInfo([],"bool",y.getTypedArrayFromDType("bool",1)),l=Z_({inputs:{a:n,b:a},backend:t});return t.disposeIntermediateTensorInfo(a),l}throw new Error(`Error in Cast: failed to cast ${n.dtype} to ${s}`)}var S2={kernelName:$o,backendName:"webgl",kernelFunc:J_};var T2="return ceil(x);",mX=ke({opSnippet:T2,packedOpSnippet:T2,cpuKernelImpl:tE}),A2={kernelName:Yo,backendName:"webgl",kernelFunc:mX};var Q_=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1815,7 +1815,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
         setOutput(clamp(value, minVal, maxVal));
       }
-    `}getCustomSetupFunc(e,t){return(n,o)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(o,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(o,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}};var av=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e,t){return(o,n)=>{this.minLoc==null&&(this.minLoc=o.getUniformLocationNoThrow(n,"minVal"),this.maxLoc=o.getUniformLocationNoThrow(n,"maxVal")),o.gl.uniform1f(this.minLoc,e),o.gl.uniform1f(this.maxLoc,t)}}};var ev=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.userCode=`
       uniform float minVal;
       uniform float maxVal;
 
@@ -1829,7 +1829,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
         setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
       }
-    `}getCustomSetupFunc(e,t){return(n,o)=>{this.minLoc==null&&(this.minLoc=n.getUniformLocationNoThrow(o,"minVal"),this.maxLoc=n.getUniformLocationNoThrow(o,"maxVal")),n.gl.uniform1f(this.minLoc,e),n.gl.uniform1f(this.maxLoc,t)}}};function G8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{clipValueMin:s,clipValueMax:a}=n,i;j().getBool("WEBGL_PACK_CLIP")?i=new av(o.shape):i=new iv(o.shape);let l=i.getCustomSetupFunc(s,a);return t.runWebGLProgram(i,[o],o.dtype,l)}var Q2={kernelName:Rn,backendName:"webgl",kernelFunc:G8};var lv=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e,t){return(o,n)=>{this.minLoc==null&&(this.minLoc=o.getUniformLocationNoThrow(n,"minVal"),this.maxLoc=o.getUniformLocationNoThrow(n,"maxVal")),o.gl.uniform1f(this.minLoc,e),o.gl.uniform1f(this.maxLoc,t)}}};function fX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{clipValueMin:s,clipValueMax:a}=o,i;W().getBool("WEBGL_PACK_CLIP")?i=new ev(n.shape):i=new Q_(n.shape);let l=i.getCustomSetupFunc(s,a);return t.runWebGLProgram(i,[n],n.dtype,l)}var E2={kernelName:Ro,backendName:"webgl",kernelFunc:fX};var tv=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
       void main() {
         float re = abs(getRealAtOutCoords());
         float im = abs(getImagAtOutCoords());
@@ -1842,27 +1842,27 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
           mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
         );
       }
-    `}};function eD(r,e){return{dataId:e.dataId,dtype:e.dtype,shape:r.shape}}function W8(r){let{inputs:e,backend:t}=r,{x:n}=e,o=t.texData.get(n.dataId),s=new lv(n.shape),a=[eD(n,o.complexTensorInfos.real),eD(n,o.complexTensorInfos.imag)];return t.runWebGLProgram(s,a,a[0].dtype)}var tD={kernelName:na,backendName:"webgl",kernelFunc:W8};var uv=class{constructor(e){this.outputShape=[],this.outputShape=S.computeOutShape(e,1),this.variableNames=e.map((a,i)=>`T${i}`);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 i=t[a-1];n.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${i}));`)}let o=t.length,s=t[t.length-1];n.push(`else setOutput(getT${o}(yR, yC-${s}));`),this.userCode=`
+    `}};function D2(r,e){return{dataId:e.dataId,dtype:e.dtype,shape:r.shape}}function dX(r){let{inputs:e,backend:t}=r,{x:o}=e,n=t.texData.get(o.dataId),s=new tv(o.shape),a=[D2(o,n.complexTensorInfos.real),D2(o,n.complexTensorInfos.imag)];return t.runWebGLProgram(s,a,a[0].dtype)}var $2={kernelName:oa,backendName:"webgl",kernelFunc:dX};var rv=class{constructor(e){this.outputShape=[],this.outputShape=N.computeOutShape(e,1),this.variableNames=e.map((a,i)=>`T${i}`);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 o=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let a=1;a<t.length;a++){let i=t[a-1];o.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${i}));`)}let n=t.length,s=t[t.length-1];o.push(`else setOutput(getT${n}(yR, yC-${s}));`),this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int yR = coords.x;
         int yC = coords.y;
 
-        ${n.join(`
+        ${o.join(`
         `)}
       }
-    `}};var cv=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=S.computeOutShape(e,t);let n=this.outputShape,o=n.length,s=Le(o),a=jt("coords",o),i=["x","y","z","w","u","v"].slice(0,o);this.variableNames=e.map((h,g)=>`T${g}`);let l=new Array(e.length-1);l[0]=e[0][t];for(let h=1;h<l.length;h++)l[h]=l[h-1]+e[h][t];let u=i[t],c=i.slice(-2),p=i.join(),m=`if (${u} < ${l[0]}) {
+    `}};var ov=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=N.computeOutShape(e,t);let o=this.outputShape,n=o.length,s=Le(n),a=Wt("coords",n),i=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((h,g)=>`T${g}`);let l=new Array(e.length-1);l[0]=e[0][t];for(let h=1;h<l.length;h++)l[h]=l[h-1]+e[h][t];let u=i[t],c=i.slice(-2),p=i.join(),m=`if (${u} < ${l[0]}) {
         return getChannel(
             getT0(${p}), vec2(${c.join()}));
         }`;for(let h=1;h<l.length;h++){let g=l[h-1];m+=`
         if (${u} < ${l[h]}  && ${u} >= ${l[h-1]}) {
           return getChannel(
-            getT${h}(${Xg(i,u,g)}),
-            vec2(${Xg(c,u,g)}));
+            getT${h}(${Hg(i,u,g)}),
+            vec2(${Hg(c,u,g)}));
         }`}let f=l.length,d=l[l.length-1];m+=`
         return getChannel(
-          getT${f}(${Xg(i,u,d)}),
-          vec2(${Xg(c,u,d)}));`,this.userCode=`
+          getT${f}(${Hg(i,u,d)}),
+          vec2(${Hg(c,u,d)}));`,this.userCode=`
       float getValue(${i.map(h=>"int "+h)}) {
         ${m}
       }
@@ -1871,34 +1871,34 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         ${s} coords = getOutputCoords();
         vec4 result = vec4(getValue(${a}), 0., 0., 0.);
 
-        ${a[o-1]} = ${a[o-1]} + 1;
-        if (${a[o-1]} < ${n[o-1]}) {
+        ${a[n-1]} = ${a[n-1]} + 1;
+        if (${a[n-1]} < ${o[n-1]}) {
           result.g = getValue(${a});
         }
 
-        ${a[o-2]} = ${a[o-2]} + 1;
-        if (${a[o-2]} < ${n[o-2]}) {
+        ${a[n-2]} = ${a[n-2]} + 1;
+        if (${a[n-2]} < ${o[n-2]}) {
           result.a = getValue(${a});
         }
 
-        ${a[o-1]} = ${a[o-1]} - 1;
-        if (${a[o-2]} < ${n[o-2]} &&
-            ${a[o-1]} < ${n[o-1]}) {
+        ${a[n-1]} = ${a[n-1]} - 1;
+        if (${a[n-2]} < ${o[n-2]} &&
+            ${a[n-1]} < ${o[n-1]}) {
           result.b = getValue(${a});
         }
         setOutput(result);
       }
-    `}};function Xg(r,e,t){let n=r.indexOf(e);return r.map((s,a)=>a===n?`${s} - ${t}`:s).join()}function tc(r){let{inputs:e,backend:t}=r,{input:n}=e,o=t.texData.get(n.dataId);return Ut({inputs:{x:o.complexTensorInfos.imag},backend:t})}var rD={kernelName:Ql,backendName:"webgl",kernelFunc:tc};function rc(r,e,t){let n=r[0].dtype;if(n==="complex64"){let u=r.map(d=>La({inputs:{input:d},backend:t})),c=r.map(d=>tc({inputs:{input:d},backend:t})),p=rc(u,e,t),m=rc(c,e,t),f=un({inputs:{real:p,imag:m},backend:t});return u.forEach(d=>t.disposeIntermediateTensorInfo(d)),c.forEach(d=>t.disposeIntermediateTensorInfo(d)),t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),f}if(n==="string"){let{tensors2D:u,outShape:c}=nD(r,e,t),p=u.map(g=>({vals:t.readSync(g.dataId),shape:g.shape})),m=u[0].shape[0]===1,f=IE(p,c,n,m),d=S.computeOutShape(r.map(g=>g.shape),e),h=t.makeTensorInfo(d,n,f);return u.forEach(g=>t.disposeIntermediateTensorInfo(g)),h}if(r.length>j().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(r.length/2),c=rc(r.slice(0,u),e,t),p=rc(r.slice(u),e,t),m=rc([c,p],e,t);return t.disposeIntermediateTensorInfo(c),t.disposeIntermediateTensorInfo(p),m}if(j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&r[0].shape.length>1){let u=new cv(r.map(c=>c.shape),e);return t.runWebGLProgram(u,r,n)}let{tensors2D:o,outShape:s}=nD(r,e,t),a=new uv(o.map(u=>u.shape)),i=t.runWebGLProgram(a,o,n);o.forEach(u=>t.disposeIntermediateTensorInfo(u));let l=pe({inputs:{x:i},attrs:{shape:s},backend:t});return t.disposeIntermediateTensorInfo(i),l}function nD(r,e,t){let n=S.computeOutShape(r.map(s=>s.shape),e);return{tensors2D:r.map(s=>pe({inputs:{x:s},attrs:{shape:[-1,y.sizeFromShape(s.shape.slice(e))]},backend:t})),outShape:n}}function pv(r){let{inputs:e,backend:t,attrs:n}=r,{axis:o}=n,s=y.parseAxisParam(o,e[0].shape)[0],a=S.computeOutShape(e.map(u=>u.shape),s);if(y.sizeFromShape(a)===0)return t.makeTensorInfo(a,e[0].dtype,[]);let i=e.filter(u=>y.sizeFromShape(u.shape)>0);if(i.length===1)return Ut({inputs:{x:i[0]},backend:t});let l=i.map(u=>u.shape);return S.assertParamsConsistent(l,s),rc(i,s,t)}var oD={kernelName:ls,backendName:"webgl",kernelFunc:pv};var Nf=class{constructor(e,t=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,i=e.padInfo.left,l=e.strideHeight,u=e.strideWidth,c=e.dilationHeight,p=e.dilationWidth,m=e.filterHeight,f=e.filterWidth,d=Math.floor(e.inChannels/4)*4,h=e.inChannels%4,g=e.dataFormat==="channelsLast",x=g?1:2,w=g?2:3,b=g?3:1,k="",_="";n&&(o?k=`float activation(float a) {
+    `}};function Hg(r,e,t){let o=r.indexOf(e);return r.map((s,a)=>a===o?`${s} - ${t}`:s).join()}function ec(r){let{inputs:e,backend:t}=r,{input:o}=e,n=t.texData.get(o.dataId);return jt({inputs:{x:n.complexTensorInfos.imag},backend:t})}var R2={kernelName:Ql,backendName:"webgl",kernelFunc:ec};function tc(r,e,t){let o=r[0].dtype;if(o==="complex64"){let u=r.map(d=>La({inputs:{input:d},backend:t})),c=r.map(d=>ec({inputs:{input:d},backend:t})),p=tc(u,e,t),m=tc(c,e,t),f=lo({inputs:{real:p,imag:m},backend:t});return u.forEach(d=>t.disposeIntermediateTensorInfo(d)),c.forEach(d=>t.disposeIntermediateTensorInfo(d)),t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),f}if(o==="string"){let{tensors2D:u,outShape:c}=F2(r,e,t),p=u.map(g=>({vals:t.readSync(g.dataId),shape:g.shape})),m=u[0].shape[0]===1,f=rE(p,c,o,m),d=N.computeOutShape(r.map(g=>g.shape),e),h=t.makeTensorInfo(d,o,f);return u.forEach(g=>t.disposeIntermediateTensorInfo(g)),h}if(r.length>W().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(r.length/2),c=tc(r.slice(0,u),e,t),p=tc(r.slice(u),e,t),m=tc([c,p],e,t);return t.disposeIntermediateTensorInfo(c),t.disposeIntermediateTensorInfo(p),m}if(W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&r[0].shape.length>1){let u=new ov(r.map(c=>c.shape),e);return t.runWebGLProgram(u,r,o)}let{tensors2D:n,outShape:s}=F2(r,e,t),a=new rv(n.map(u=>u.shape)),i=t.runWebGLProgram(a,n,o);n.forEach(u=>t.disposeIntermediateTensorInfo(u));let l=pe({inputs:{x:i},attrs:{shape:s},backend:t});return t.disposeIntermediateTensorInfo(i),l}function F2(r,e,t){let o=N.computeOutShape(r.map(s=>s.shape),e);return{tensors2D:r.map(s=>pe({inputs:{x:s},attrs:{shape:[-1,y.sizeFromShape(s.shape.slice(e))]},backend:t})),outShape:o}}function nv(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o,s=y.parseAxisParam(n,e[0].shape)[0],a=N.computeOutShape(e.map(u=>u.shape),s);if(y.sizeFromShape(a)===0)return t.makeTensorInfo(a,e[0].dtype,[]);let i=e.filter(u=>y.sizeFromShape(u.shape)>0);if(i.length===1)return jt({inputs:{x:i[0]},backend:t});let l=i.map(u=>u.shape);return N.assertParamsConsistent(l,s),tc(i,s,t)}var O2={kernelName:ls,backendName:"webgl",kernelFunc:nv};var If=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,i=e.padInfo.left,l=e.strideHeight,u=e.strideWidth,c=e.dilationHeight,p=e.dilationWidth,m=e.filterHeight,f=e.filterWidth,d=Math.floor(e.inChannels/4)*4,h=e.inChannels%4,g=e.dataFormat==="channelsLast",x=g?1:2,b=g?2:3,w=g?3:1,k="",_="";o&&(n?k=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
-          ${n}
+          ${o}
         }`:s?k=`float activation(float a) {
           float b = getLeakyreluAlphaAtOutCoords();
-          ${n}
+          ${o}
         }`:k=`
           float activation(float x) {
-            ${n}
+            ${o}
           }
-        `,_="result = activation(result);");let A=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
+        `,_="result = activation(result);");let D=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${k}
 
       const ivec2 strides = ivec2(${l}, ${u});
@@ -1907,10 +1907,10 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
       void main() {
         ivec4 coords = getOutputCoords();
         int batch = coords[0];
-        int d2 = coords[${b}];
+        int d2 = coords[${w}];
 
         ivec2 xRCCorner =
-            ivec2(coords[${x}], coords[${w}]) * strides - pads;
+            ivec2(coords[${x}], coords[${b}]) * strides - pads;
         int xRCorner = xRCCorner.x;
         int xCCorner = xRCCorner.y;
 
@@ -2018,13 +2018,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
 
         float result = dotProd;
-        ${A}
+        ${D}
         ${_}
         setOutput(result);
       }
-    `}},mv=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,o=e.padInfo.left,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,p=e.filterDepth,m=e.filterHeight,f=e.filterWidth,d=Math.floor(e.inChannels/4)*4,h=e.inChannels%4;this.userCode=`
+    `}},sv=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,o=e.padInfo.top,n=e.padInfo.left,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,p=e.filterDepth,m=e.filterHeight,f=e.filterWidth,d=Math.floor(e.inChannels/4)*4,h=e.inChannels%4;this.userCode=`
       const ivec3 strides = ivec3(${s}, ${a}, ${i});
-      const ivec3 pads = ivec3(${t}, ${n}, ${o});
+      const ivec3 pads = ivec3(${t}, ${o}, ${n});
 
       void main() {
         ivec5 coords = getOutputCoords();
@@ -2110,31 +2110,31 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};var fv=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:o,inChannels:s,strideWidth:a,strideHeight:i,padInfo:l,outWidth:u,dilationWidth:c,dilationHeight:p,dataFormat:m}=n,{left:f,top:d}=l,h=s*o,g=Ft(),x=m==="channelsLast",w=x?0:1,b=x?1:2,k="";for(let _=0;_<=1;_++)for(let A=0;A<=1;A++)k+=`
-          blockIndex = rc.y + ${A};
+    `}};var iv=class{constructor(e,t,o){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:n,inChannels:s,strideWidth:a,strideHeight:i,padInfo:l,outWidth:u,dilationWidth:c,dilationHeight:p,dataFormat:m}=o,{left:f,top:d}=l,h=s*n,g=Rt(),x=m==="channelsLast",b=x?0:1,w=x?1:2,k="";for(let _=0;_<=1;_++)for(let D=0;D<=1;D++)k+=`
+          blockIndex = rc.y + ${D};
           pos = rc.x + ${_};
 
           if(blockIndex < ${e[1]} && pos < ${e[0]}) {
             offsetY = int(blockIndex / (${u})) * ${i} - ${d};
             d0 = offsetY + ${p} * (pos / ${h});
 
-            if(d0 < ${t[w]} && d0 >= 0) {
+            if(d0 < ${t[b]} && d0 >= 0) {
 
               offsetX = int(mod(float(blockIndex), ${u}.) * ${a}. - ${f}.);
               d1 = offsetX + ${c} * (int(mod(float(pos), ${h}.) / ${s}.));
 
-              if(d1 < ${t[b]} && d1 >= 0) {
+              if(d1 < ${t[w]} && d1 >= 0) {
 
                 ch = int(mod(float(pos), ${s}.));
 
                 if (${x}) {
                   innerDims = vec2(d1, ch);
-                  result[${_*2+A}] = getChannel(
+                  result[${_*2+D}] = getChannel(
                     getA(d0, int(innerDims.x),
                     int(innerDims.y)), innerDims);
                 } else {
                   innerDims = vec2(d0, d1);
-                  result[${_*2+A}] = getChannel(
+                  result[${_*2+D}] = getChannel(
                     getA(ch, int(innerDims.x),
                     int(innerDims.y)), innerDims);
                 }
@@ -2154,7 +2154,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
         ${g.output} = result;
       }
-    `}};function Yg({x:r,filter:e,convInfo:t,backend:n,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let l=r.shape,u=n.texData.get(r.dataId),c=t.inChannels,p=l[0]*l[1]*l[2],m=t.outChannels,f=t.dataFormat==="channelsLast",d=!1,h=!1,g,x=[],w=(p===1||m===1)&&c>H_,b=l[2]%2!=0&&!!u.isPacked;if(w||!j().getBool("WEBGL_LAZILY_UNPACK")||!j().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!b){let k=f?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=pe({inputs:{x:r},backend:n,attrs:{shape:[1,k,t.inChannels]}}),A=pe({inputs:{x:e},backend:n,attrs:{shape:[1,t.inChannels,t.outChannels]}}),N=Qu({a:_,b:A,transposeA:d,transposeB:h,backend:n,bias:o,activation:i,preluActivationWeights:s,leakyreluAlpha:a});g=pe({inputs:{x:N},backend:n,attrs:{shape:t.outShape}}),x.push(_),x.push(A),x.push(N)}else{let k=f?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:r.dataId,shape:[1,k,t.inChannels],dtype:r.dtype},A=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,y.assert(dl(u.shape,_.shape),()=>`packed reshape ${u.shape} to ${_.shape} isn't free`);let N=pe({inputs:{x:e},backend:n,attrs:{shape:[1,t.inChannels,t.outChannels]}});x.push(N);let $=Qu({a:_,b:N,backend:n,transposeA:d,transposeB:h,bias:o,activation:i,preluActivationWeights:s,leakyreluAlpha:a}),F=n.texData.get($.dataId);y.assert(F.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=A,F.shape=t.outShape,g=Ut({inputs:{x:$},backend:n}),g.shape=t.outShape,x.push($)}for(let k of x)n.disposeIntermediateTensorInfo(k);return g}function Zg({x:r,filter:e,convInfo:t,backend:n,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:p,outHeight:m,dataFormat:f}=t,d=f==="channelsLast",h=l*u*c,g=m*p,x=[h,g],w=!0,b=!1,k=[],_=pe({inputs:{x:r},backend:n,attrs:{shape:r.shape.slice(1)}}),A=pe({inputs:{x:e},backend:n,attrs:{shape:[1,h,y.sizeFromShape(e.shape)/h]}});k.push(_),k.push(A);let N=new fv(x,_.shape,t),$=n.runWebGLProgram(N,[_],"float32"),F=pe({inputs:{x:$},backend:n,attrs:{shape:[1,x[0],x[1]]}});k.push($),k.push(F);let M=o!=null,V=s!=null,W=i==="leakyrelu",U=i?gl(i,!0):null,H=new Cf(F.shape,A.shape,[1,g,t.outChannels],w,b,M,U,V,W),q=[F,A];if(o&&q.push(o),V&&q.push(s),W){let re=n.makeTensorInfo([],"float32",y.createScalarValue(a,"float32"));q.push(re),k.push(re)}let X=n.runWebGLProgram(H,q,"float32"),ne=d?[1,m,p,t.outChannels]:[1,t.outChannels,m,p],Y=pe({inputs:{x:X},backend:n,attrs:{shape:ne}});k.push(X);for(let re of k)n.disposeIntermediateTensorInfo(re);return Y}function j8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,filter:s}=e,{strides:a,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=n,p=S.convertConv2DDataFormat(l),m=S.computeConv2DInfo(o.shape,s.shape,a,u,i,c,!1,p),f;if(m.filterHeight===1&&m.filterWidth===1&&m.dilationHeight===1&&m.dilationWidth===1&&m.strideHeight===1&&m.strideWidth===1&&(m.padInfo.type==="SAME"||m.padInfo.type==="VALID"))f=Yg({x:o,filter:s,convInfo:m,backend:t});else if(j().getBool("WEBGL_CONV_IM2COL")&&o.shape[0]===1)f=Zg({x:o,filter:s,convInfo:m,backend:t});else{let h=new Nf(m);f=t.runWebGLProgram(h,[o,s],"float32")}let d=pe({inputs:{x:f},backend:t,attrs:{shape:m.outShape}});return t.disposeIntermediateTensorInfo(f),d}var sD={kernelName:Zn,backendName:"webgl",kernelFunc:j8};var dv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,o=e.padInfo.top,s=e.padInfo.left,a=e.dataFormat==="channelsLast";this.userCode=`
+    `}};function qg({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let l=r.shape,u=o.texData.get(r.dataId),c=t.inChannels,p=l[0]*l[1]*l[2],m=t.outChannels,f=t.dataFormat==="channelsLast",d=!1,h=!1,g,x=[],b=(p===1||m===1)&&c>z_,w=l[2]%2!=0&&!!u.isPacked;if(b||!W().getBool("WEBGL_LAZILY_UNPACK")||!W().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let k=f?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],_=pe({inputs:{x:r},backend:o,attrs:{shape:[1,k,t.inChannels]}}),D=pe({inputs:{x:e},backend:o,attrs:{shape:[1,t.inChannels,t.outChannels]}}),T=Ju({a:_,b:D,transposeA:d,transposeB:h,backend:o,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a});g=pe({inputs:{x:T},backend:o,attrs:{shape:t.outShape}}),x.push(_),x.push(D),x.push(T)}else{let k=f?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),_={dataId:r.dataId,shape:[1,k,t.inChannels],dtype:r.dtype},D=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,y.assert(dl(u.shape,_.shape),()=>`packed reshape ${u.shape} to ${_.shape} isn't free`);let T=pe({inputs:{x:e},backend:o,attrs:{shape:[1,t.inChannels,t.outChannels]}});x.push(T);let R=Ju({a:_,b:T,backend:o,transposeA:d,transposeB:h,bias:n,activation:i,preluActivationWeights:s,leakyreluAlpha:a}),O=o.texData.get(R.dataId);y.assert(O.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=D,O.shape=t.outShape,g=jt({inputs:{x:R},backend:o}),g.shape=t.outShape,x.push(R)}for(let k of x)o.disposeIntermediateTensorInfo(k);return g}function Kg({x:r,filter:e,convInfo:t,backend:o,bias:n=null,preluActivationWeights:s=null,leakyreluAlpha:a=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:p,outHeight:m,dataFormat:f}=t,d=f==="channelsLast",h=l*u*c,g=m*p,x=[h,g],b=!0,w=!1,k=[],_=pe({inputs:{x:r},backend:o,attrs:{shape:r.shape.slice(1)}}),D=pe({inputs:{x:e},backend:o,attrs:{shape:[1,h,y.sizeFromShape(e.shape)/h]}});k.push(_),k.push(D);let T=new iv(x,_.shape,t),R=o.runWebGLProgram(T,[_],"float32"),O=pe({inputs:{x:R},backend:o,attrs:{shape:[1,x[0],x[1]]}});k.push(R),k.push(O);let M=n!=null,G=s!=null,j=i==="leakyrelu",U=i?gl(i,!0):null,H=new vf(O.shape,D.shape,[1,g,t.outChannels],b,w,M,U,G,j),q=[O,D];if(n&&q.push(n),G&&q.push(s),j){let re=o.makeTensorInfo([],"float32",y.createScalarValue(a,"float32"));q.push(re),k.push(re)}let X=o.runWebGLProgram(H,q,"float32"),oe=d?[1,m,p,t.outChannels]:[1,t.outChannels,m,p],Y=pe({inputs:{x:X},backend:o,attrs:{shape:oe}});k.push(X);for(let re of k)o.disposeIntermediateTensorInfo(re);return Y}function hX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=o,p=N.convertConv2DDataFormat(l),m=N.computeConv2DInfo(n.shape,s.shape,a,u,i,c,!1,p),f;if(m.filterHeight===1&&m.filterWidth===1&&m.dilationHeight===1&&m.dilationWidth===1&&m.strideHeight===1&&m.strideWidth===1&&(m.padInfo.type==="SAME"||m.padInfo.type==="VALID"))f=qg({x:n,filter:s,convInfo:m,backend:t});else if(W().getBool("WEBGL_CONV_IM2COL")&&n.shape[0]===1)f=Kg({x:n,filter:s,convInfo:m,backend:t});else{let h=new If(m);f=t.runWebGLProgram(h,[n,s],"float32")}let d=pe({inputs:{x:f},backend:t,attrs:{shape:m.outShape}});return t.disposeIntermediateTensorInfo(f),d}var P2={kernelName:Zo,backendName:"webgl",kernelFunc:hX};var av=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,o=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a=e.dataFormat==="channelsLast";this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2168,14 +2168,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
         for (int b = 0; b < ${e.batchSize}; b++) {
           for (int yR = 0; yR < ${e.outHeight}; yR++) {
-            int xR = wR + yR * ${t} - ${o};
+            int xR = wR + yR * ${t} - ${n};
 
             if (xR < 0 || xR >= ${e.inHeight}) {
               continue;
             }
 
             for (int yC = 0; yC < ${e.outWidth}; yC++) {
-              int xC = wC + yC * ${n} - ${s};
+              int xC = wC + yC * ${o} - ${s};
 
               if (xC < 0 || xC >= ${e.inWidth}) {
                 continue;
@@ -2196,7 +2196,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},hv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,o=e.strideHeight,s=e.strideWidth,a=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,l=n-1-e.padInfo.left,u=a?1:2,c=a?2:3,p=a?3:1;this.userCode=`
+    `}},lv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,l=o-1-e.padInfo.left,u=a?1:2,c=a?2:3,p=a?3:1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${l});
 
       void main() {
@@ -2212,7 +2212,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         // ? = 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) / ${o}.0;
+          float dyR = float(dyRCorner + wR) / ${n}.0;
 
           if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
             continue;
@@ -2221,7 +2221,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
           int wRPerm = ${t} - 1 - wR;
 
-          for (int wC = 0; wC < ${n}; wC++) {
+          for (int wC = 0; wC < ${o}; wC++) {
             float dyC = float(dyCCorner + wC) / ${s}.0;
 
             if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
@@ -2230,7 +2230,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
             }
             int idyC = int(dyC);
 
-            int wCPerm = ${n} - 1 - wC;
+            int wCPerm = ${o} - 1 - wC;
 
             for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
 
@@ -2249,7 +2249,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},gv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,o=e.strideWidth,s=e.padInfo.front,a=e.padInfo.top,i=e.padInfo.left;this.userCode=`
+    `}},uv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,o=e.strideHeight,n=e.strideWidth,s=e.padInfo.front,a=e.padInfo.top,i=e.padInfo.left;this.userCode=`
       void main() {
         ivec5 coords = getOutputCoords();
         int wF = coords.x;
@@ -2269,14 +2269,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
             }
 
             for (int yR = 0; yR < ${e.outHeight}; yR++) {
-              int xR = wR + yR * ${n} - ${a};
+              int xR = wR + yR * ${o} - ${a};
 
               if (xR < 0 || xR >= ${e.inHeight}) {
                 continue;
               }
 
               for (int yC = 0; yC < ${e.outWidth}; yC++) {
-                int xC = wC + yC * ${o} - ${i};
+                int xC = wC + yC * ${n} - ${i};
 
                 if (xC < 0 || xC >= ${e.inWidth}) {
                   continue;
@@ -2291,7 +2291,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},xv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,o=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=t-1-e.padInfo.front,u=n-1-e.padInfo.top,c=o-1-e.padInfo.left;this.userCode=`
+    `}},cv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,o=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,i=e.strideWidth,l=t-1-e.padInfo.front,u=o-1-e.padInfo.top,c=n-1-e.padInfo.left;this.userCode=`
       const ivec3 pads = ivec3(${l}, ${u}, ${c});
 
       void main() {
@@ -2316,7 +2316,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
           int wFPerm = ${t} - 1 - wF;
 
-          for (int wR = 0; wR < ${n}; wR++) {
+          for (int wR = 0; wR < ${o}; wR++) {
             float dyR = float(dyRCorner + wR) / ${a}.0;
 
             if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
@@ -2325,9 +2325,9 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
             }
             int idyR = int(dyR);
 
-            int wRPerm = ${n} - 1 - wR;
+            int wRPerm = ${o} - 1 - wR;
 
-            for (int wC = 0; wC < ${o}; wC++) {
+            for (int wC = 0; wC < ${n}; wC++) {
               float dyC = float(dyCCorner + wC) / ${i}.0;
 
               if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
@@ -2336,7 +2336,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
               }
               int idyC = int(dyC);
 
-              int wCPerm = ${o} - 1 - wC;
+              int wCPerm = ${n} - 1 - wC;
 
               for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
                 float xValue = getDy(batch, idyF, idyR, idyC, d2);
@@ -2348,14 +2348,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function U8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,dy:s}=e,{strides:a,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=n,p=S.convertConv2DDataFormat(l),m=S.computeConv2DInfo(o.shape,c,a,1,i,u,!1,p),f=new dv(m);return t.runWebGLProgram(f,[o,s],"float32")}var iD={kernelName:Wl,backendName:"webgl",kernelFunc:U8};function H8(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,filter:s}=e,{inputShape:a,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=n,p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(a,s.shape,i,1,l,c,!1,p),f=new hv(m);return t.runWebGLProgram(f,[o,s],"float32")}var aD={kernelName:Jn,backendName:"webgl",kernelFunc:H8};function q8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,filter:s}=e,{strides:a,pad:i,dilations:l}=n,u=S.computeConv3DInfo(o.shape,s.shape,a,l,i),c=new mv(u);return t.runWebGLProgram(c,[o,s],"float32")}var lD={kernelName:oa,backendName:"webgl",kernelFunc:q8};function K8(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,dy:s}=e,{strides:a,pad:i,filterShape:l}=n,u=S.computeConv3DInfo(o.shape,l,a,1,i),c=new gv(u);return t.runWebGLProgram(c,[o,s],"float32")}var uD={kernelName:jl,backendName:"webgl",kernelFunc:K8};function X8(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,filter:s}=e,{pad:a,strides:i,inputShape:l}=n,u=S.computeConv3DInfo(l,s.shape,i,1,a),c=new xv(u);return t.runWebGLProgram(c,[o,s],"float32")}var cD={kernelName:Ul,backendName:"webgl",kernelFunc:X8};var Y8=jg+`
+    `}};function gX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=o,p=N.convertConv2DDataFormat(l),m=N.computeConv2DInfo(n.shape,c,a,1,i,u,!1,p),f=new av(m);return t.runWebGLProgram(f,[n,s],"float32")}var M2={kernelName:Wl,backendName:"webgl",kernelFunc:gX};function xX(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{inputShape:a,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=o,p=N.convertConv2DDataFormat(u),m=N.computeConv2DInfo(a,s.shape,i,1,l,c,!1,p),f=new lv(m);return t.runWebGLProgram(f,[n,s],"float32")}var L2={kernelName:Jo,backendName:"webgl",kernelFunc:xX};function yX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l}=o,u=N.computeConv3DInfo(n.shape,s.shape,a,l,i),c=new sv(u);return t.runWebGLProgram(c,[n,s],"float32")}var z2={kernelName:na,backendName:"webgl",kernelFunc:yX};function bX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,pad:i,filterShape:l}=o,u=N.computeConv3DInfo(n.shape,l,a,1,i),c=new uv(u);return t.runWebGLProgram(c,[n,s],"float32")}var B2={kernelName:jl,backendName:"webgl",kernelFunc:bX};function wX(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{pad:a,strides:i,inputShape:l}=o,u=N.computeConv3DInfo(l,s.shape,i,1,a),c=new cv(u);return t.runWebGLProgram(c,[n,s],"float32")}var V2={kernelName:Ul,backendName:"webgl",kernelFunc:wX};var kX=Vg+`
   return cos(x);
-`,Z8=ke({opSnippet:Y8}),pD={kernelName:Qn,backendName:"webgl",kernelFunc:Z8};var J8=`
+`,_X=ke({opSnippet:kX}),G2={kernelName:Qo,backendName:"webgl",kernelFunc:_X};var vX=`
   float e2x = exp(-x);
   return (e2x + 1.0 / e2x) / 2.0;
-`,Q8=ke({opSnippet:J8}),mD={kernelName:ei,backendName:"webgl",kernelFunc:Q8};var yv=class{constructor(e,t,n,o,s){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,i,l,u]=e,[c]=t,[p,m]=n;this.outputShape=[c,p,m,u];let f=o==="bilinear"?1:0,[d,h]=[`${i-1}.0`,`${l-1}.0`],[g,x,w]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${d} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${d}`],[b,k,_]=m>1?[`${(l-1)/(m-1)}`,"(x2-x1) * width_ratio",`x1*${h} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${h}`];this.userCode=`
+`,CX=ke({opSnippet:vX}),W2={kernelName:ei,backendName:"webgl",kernelFunc:CX};var pv=class{constructor(e,t,o,n,s){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,i,l,u]=e,[c]=t,[p,m]=o;this.outputShape=[c,p,m,u];let f=n==="bilinear"?1:0,[d,h]=[`${i-1}.0`,`${l-1}.0`],[g,x,b]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${d} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${d}`],[w,k,_]=m>1?[`${(l-1)/(m-1)}`,"(x2-x1) * width_ratio",`x1*${h} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${h}`];this.userCode=`
       const float height_ratio = float(${g});
-      const float width_ratio = float(${b});
+      const float width_ratio = float(${w});
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -2378,7 +2378,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         float height_scale = ${x};
         float width_scale = ${k};
 
-        float in_y = ${w};
+        float in_y = ${b};
         if( in_y < 0.0 || in_y > ${d} ) {
           setOutput(float(${s}));
           return;
@@ -2414,21 +2414,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
           setOutput(newValue);
         }
       }
-    `}};var eX=r=>{let{inputs:e,backend:t,attrs:n}=r,{image:o,boxes:s,boxInd:a}=e,{cropSize:i,method:l,extrapolationValue:u}=n,c=new yv(o.shape,s.shape,i,l,u);return t.runWebGLProgram(c,[o,s,a],"float32")},fD={kernelName:ti,backendName:"webgl",kernelFunc:eX};var Jg=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let o=e.length,s=t?"0.0":`getX(${dD(o,"coords")})`,a=e[e.length-1],i="",l="";t?(i=n?`end != ${a-1}`:"end != 0",l=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${a}`:"end >= pow2",l=n?"end + pow2":"end - pow2"),this.userCode=`
+    `}};var IX=r=>{let{inputs:e,backend:t,attrs:o}=r,{image:n,boxes:s,boxInd:a}=e,{cropSize:i,method:l,extrapolationValue:u}=o,c=new pv(n.shape,s.shape,i,l,u);return t.runWebGLProgram(c,[n,s,a],"float32")},j2={kernelName:ti,backendName:"webgl",kernelFunc:IX};var Xg=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=e;let n=e.length,s=t?"0.0":`getX(${U2(n,"coords")})`,a=e[e.length-1],i="",l="";t?(i=o?`end != ${a-1}`:"end != 0",l=o?"end + 1":"end - 1"):(i=o?`end + pow2 < ${a}`:"end >= pow2",l=o?"end + pow2":"end - pow2"),this.userCode=`
       uniform float index;
       void main() {
-        ${Le(o)} coords = getOutputCoords();
-        int end = ${hD(o,"coords")};
+        ${Le(n)} coords = getOutputCoords();
+        int end = ${H2(n,"coords")};
         float val = ${s};
         int pow2 = int(pow(2.0, index));
         if (${i}) {
           int idx = ${l};
-          ${hD(o,"coords")} = idx;
-          val += getX(${dD(o,"coords")});
+          ${H2(n,"coords")} = idx;
+          val += getX(${U2(n,"coords")});
         }
         setOutput(val);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function dD(r,e){if(r===1)return`${e}`;if(r===2)return`${e}.x, ${e}.y`;if(r===3)return`${e}.x, ${e}.y, ${e}.z`;if(r===4)return`${e}.x, ${e}.y, ${e}.z, ${e}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function hD(r,e){if(r===1)return`${e}`;if(r===2)return`${e}.y`;if(r===3)return`${e}.z`;if(r===4)return`${e}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function tX(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{axis:s,exclusive:a,reverse:i}=n,l=o.shape.length,u=S.getAxesPermutation([s],l),c=o;u!=null&&(c=Lt({inputs:{x:o},backend:t,attrs:{perm:u}}));let p=S.getInnerMostAxes(1,l)[0];if(p!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${o.shape.length-1} but got axis=${s}`);let m=c.shape[p],f=Ut({inputs:{x:c},backend:t});for(let d=0;d<=Math.ceil(Math.log2(m))-1;d++){let h=new Jg(c.shape,!1,i),g=h.getCustomSetupFunc(d),x=f;f=t.runWebGLProgram(h,[f],f.dtype,g),t.disposeIntermediateTensorInfo(x)}if(a){let d=new Jg(c.shape,a,i),h=f;f=t.runWebGLProgram(d,[f],f.dtype),t.disposeIntermediateTensorInfo(h)}if(u!=null){let d=S.getUndoAxesPermutation(u),h=Lt({inputs:{x:f},backend:t,attrs:{perm:d}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(c),h}return f}var gD={kernelName:eo,backendName:"webgl",kernelFunc:tX};function rX(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,weights:s}=e,{size:a,binaryOutput:i}=n;if(o.shape.length===1){let l=t.readSync(o.dataId),u=t.readSync(s.dataId),c=Bg(l,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(o.shape.length===2){let l=t.bufferSync(o),u=t.bufferSync(s),c=vE(l,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${o.shape.length}.`)}var xD={kernelName:Hl,backendName:"webgl",kernelFunc:rX};var bv=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,o)=>{this.index==null&&(this.index=t.getUniformLocation(o,"index")),t.gl.uniform1f(this.index,e)}}};function U2(r,e){if(r===1)return`${e}`;if(r===2)return`${e}.x, ${e}.y`;if(r===3)return`${e}.x, ${e}.y, ${e}.z`;if(r===4)return`${e}.x, ${e}.y, ${e}.z, ${e}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function H2(r,e){if(r===1)return`${e}`;if(r===2)return`${e}.y`;if(r===3)return`${e}.z`;if(r===4)return`${e}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function NX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,exclusive:a,reverse:i}=o,l=n.shape.length,u=N.getAxesPermutation([s],l),c=n;u!=null&&(c=Mt({inputs:{x:n},backend:t,attrs:{perm:u}}));let p=N.getInnerMostAxes(1,l)[0];if(p!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${n.shape.length-1} but got axis=${s}`);let m=c.shape[p],f=jt({inputs:{x:c},backend:t});for(let d=0;d<=Math.ceil(Math.log2(m))-1;d++){let h=new Xg(c.shape,!1,i),g=h.getCustomSetupFunc(d),x=f;f=t.runWebGLProgram(h,[f],f.dtype,g),t.disposeIntermediateTensorInfo(x)}if(a){let d=new Xg(c.shape,a,i),h=f;f=t.runWebGLProgram(d,[f],f.dtype),t.disposeIntermediateTensorInfo(h)}if(u!=null){let d=N.getUndoAxesPermutation(u),h=Mt({inputs:{x:f},backend:t,attrs:{perm:d}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(c),h}return f}var q2={kernelName:en,backendName:"webgl",kernelFunc:NX};function SX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,weights:s}=e,{size:a,binaryOutput:i}=o;if(n.shape.length===1){let l=t.readSync(n.dataId),u=t.readSync(s.dataId),c=Mg(l,u,s.dtype,s.shape,a);return t.makeTensorInfo([a],s.dtype,c)}else if(n.shape.length===2){let l=t.bufferSync(n),u=t.bufferSync(s),c=eE(l,u,a,i);return t.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${n.shape.length}.`)}var K2={kernelName:Hl,backendName:"webgl",kernelFunc:SX};var mv=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=o,this.userCode=`
     void main() {
       ivec4 coords = getOutputCoords();
       int b = coords[0];
@@ -2447,17 +2447,17 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
       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 nX(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{blockSize:s,dataFormat:a}=n;y.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let i=o.shape[0],l=a==="NHWC"?o.shape[1]:o.shape[2],u=a==="NHWC"?o.shape[2]:o.shape[3],c=a==="NHWC"?o.shape[3]:o.shape[1],p=l*s,m=u*s,f=c/(s*s),d=a==="NHWC"?[i,p,m,f]:[i,f,p,m],h=new bv(d,s,a);return t.runWebGLProgram(h,[o],o.dtype)}var yD={kernelName:ri,backendName:"webgl",kernelFunc:nX};var Sf=class{constructor(e,t=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,p=e.strideWidth,m=e.dilationHeight,f=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,g=e.outChannels/e.inChannels,x="",w="";n&&(o?x=`float activation(float a) {
+  `}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 TX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockSize:s,dataFormat:a}=o;y.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let i=n.shape[0],l=a==="NHWC"?n.shape[1]:n.shape[2],u=a==="NHWC"?n.shape[2]:n.shape[3],c=a==="NHWC"?n.shape[3]:n.shape[1],p=l*s,m=u*s,f=c/(s*s),d=a==="NHWC"?[i,p,m,f]:[i,f,p,m],h=new mv(d,s,a);return t.runWebGLProgram(h,[n],n.dtype)}var X2={kernelName:ri,backendName:"webgl",kernelFunc:TX};var Nf=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,p=e.strideWidth,m=e.dilationHeight,f=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,g=e.outChannels/e.inChannels,x="",b="";o&&(n?x=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
-          ${n}
+          ${o}
         }`:s?x=`float activation(float a) {
           float b = getLeakyreluAlphaAtOutCoords();
-          ${n}
+          ${o}
         }`:x=`
           float activation(float x) {
-            ${n}
+            ${o}
           }
-        `,w="result = activation(result);");let b=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
+        `,b="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${x}
 
       const ivec2 strides = ivec2(${c}, ${p});
@@ -2499,28 +2499,28 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
 
         float result = dotProd;
-        ${b}
         ${w}
+        ${b}
         setOutput(result);
       }
-    `}};var Tf=class{constructor(e,t=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let a=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,p=e.strideWidth,m=e.dilationHeight,f=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,g=h,x="int xR; int xC; int xCOffset;";for(let _=0;_<d;_++)for(let A=0;A<h;A++)x+=`
-          vec4 xTexelR${_}C${A*2} = vec4(0.);
-          vec4 wR${_}C${A} = vec4(0.);
-          vec4 xR${_}C${A} = vec4(0.);`;for(let _=0;_<d;_++)for(let A=0;A<g;A++){let N=A*2;if(x+=`
+    `}};var Sf=class{constructor(e,t=!1,o=null,n=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let a=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,p=e.strideWidth,m=e.dilationHeight,f=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,g=h,x="int xR; int xC; int xCOffset;";for(let _=0;_<d;_++)for(let D=0;D<h;D++)x+=`
+          vec4 xTexelR${_}C${D*2} = vec4(0.);
+          vec4 wR${_}C${D} = vec4(0.);
+          vec4 xR${_}C${D} = vec4(0.);`;for(let _=0;_<d;_++)for(let D=0;D<g;D++){let T=D*2;if(x+=`
           xR = xRCorner + ${_*m};
-          xC = xCCorner + ${N*f};
-        `,p===1){if(N<h&&(u%2==1?x+=`
+          xC = xCCorner + ${T*f};
+        `,p===1){if(T<h&&(u%2==1?x+=`
                 xCOffset = xC + 1;
                 if(xR >= 0 && xR < ${a} && xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${_}C${N} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${_}C${T} = getX(batch, xR, xCOffset, d1);
 
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if(xCOffset + 1 >= ${i}) {
-                    xTexelR${_}C${N}.zw = vec2(0.);
+                    xTexelR${_}C${T}.zw = vec2(0.);
                   }
                 } else {
-                  xTexelR${_}C${N} = vec4(0.);
+                  xTexelR${_}C${T} = vec4(0.);
                 }
 
                 xCOffset = xC + 1 - 2;
@@ -2533,105 +2533,105 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
                     previous.zw = vec2(0.);
                   }
 
-                  xR${_}C${N} = vec4(previous.zw, xTexelR${_}C${N}.xy);
+                  xR${_}C${T} = vec4(previous.zw, xTexelR${_}C${T}.xy);
                 } else {
-                  xR${_}C${N} = vec4(0, 0, xTexelR${_}C${N}.xy);
+                  xR${_}C${T} = vec4(0, 0, xTexelR${_}C${T}.xy);
                 }
               `:x+=`
                 if(xR >= 0 && xR < ${a} && xC >= 0 && xC < ${i}) {
-                  xTexelR${_}C${N} = getX(batch, xR, xC, d1);
+                  xTexelR${_}C${T} = getX(batch, xR, xC, d1);
                 } else {
-                  xTexelR${_}C${N} = vec4(0.);
+                  xTexelR${_}C${T} = vec4(0.);
                 }
 
-                xR${_}C${N} = xTexelR${_}C${N};
-              `,N+1<h)){let $=u%2==0?y.nearestLargerEven(f):f;f%2==0&&u%2==1||f%2!=0&&u%2!=1?(x+=`
-                  xCOffset = xC + ${u%2} + ${$};
+                xR${_}C${T} = xTexelR${_}C${T};
+              `,T+1<h)){let R=u%2==0?y.nearestLargerEven(f):f;f%2==0&&u%2==1||f%2!=0&&u%2!=1?(x+=`
+                  xCOffset = xC + ${u%2} + ${R};
 
                   if(xR >= 0 && xR < ${a} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
-                    xTexelR${_}C${N+2} = getX(batch, xR, xCOffset, d1);
+                    xTexelR${_}C${T+2} = getX(batch, xR, xCOffset, d1);
                   }
                 `,f>1&&(x+=`
                     xCOffset -= 2;
                     if(xR >= 0 && xR < ${a} &&
                       xCOffset >= 0 && xCOffset < ${i}) {
-                      xTexelR${_}C${N} = getX(batch, xR, xCOffset, d1);
+                      xTexelR${_}C${T} = getX(batch, xR, xCOffset, d1);
                     } else {
-                      xTexelR${_}C${N} = vec4(0.);
+                      xTexelR${_}C${T} = vec4(0.);
                     }
                   `),x+=`
-                  xR${_}C${N+1} = vec4(
-                    xTexelR${_}C${N}.zw, xTexelR${_}C${N+2}.xy);
+                  xR${_}C${T+1} = vec4(
+                    xTexelR${_}C${T}.zw, xTexelR${_}C${T+2}.xy);
                 `):x+=`
-                  xCOffset = xC + ${$};
+                  xCOffset = xC + ${R};
 
                   if(xR >= 0 && xR < ${a} &&
                     xCOffset >= 0 && xCOffset < ${i}) {
-                    xTexelR${_}C${N+2} = getX(batch, xR, xCOffset, d1);
+                    xTexelR${_}C${T+2} = getX(batch, xR, xCOffset, d1);
                   }
 
-                  xR${_}C${N+1} = xTexelR${_}C${N+2};
-                `}}else N<h&&(x+=`
+                  xR${_}C${T+1} = xTexelR${_}C${T+2};
+                `}}else T<h&&(x+=`
               if(xR >= 0 && xR < ${a}) {
             `,u%2==1?(x+=`
                 xCOffset = xC + 1 - ${p};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${_}C${N} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${_}C${T} = getX(batch, xR, xCOffset, d1);
                 } else {
-                  xTexelR${_}C${N} = vec4(0.);
+                  xTexelR${_}C${T} = vec4(0.);
                 }
 
                 if(xC + 1 >= 0 && xC + 1 < ${i}) {
-                  xTexelR${_}C${N+2} = getX(batch, xR, xC + 1, d1);
+                  xTexelR${_}C${T+2} = getX(batch, xR, xC + 1, d1);
                 } else {
-                  xTexelR${_}C${N+2} = vec4(0.);
+                  xTexelR${_}C${T+2} = vec4(0.);
                 }
 
-                xR${_}C${N} = vec4(
-                  xTexelR${_}C${N}.zw, xTexelR${_}C${N+2}.zw);
-              `,N+1<h&&(x+=`
+                xR${_}C${T} = vec4(
+                  xTexelR${_}C${T}.zw, xTexelR${_}C${T+2}.zw);
+              `,T+1<h&&(x+=`
                   vec4 final = vec4(0.);
                   xCOffset = xC + 1 + ${p};
                   if(xCOffset >= 0 && xCOffset < ${i}) {
                     final = getX(batch, xR, xCOffset, d1);
                   }
-                  xR${_}C${N+1} = vec4(xTexelR${_}C${N+2}.xy, final.xy);
+                  xR${_}C${T+1} = vec4(xTexelR${_}C${T+2}.xy, final.xy);
                 `)):(x+=`
                 if(xC >= 0 && xC < ${i}) {
-                  xTexelR${_}C${N} = getX(batch, xR, xC, d1);
+                  xTexelR${_}C${T} = getX(batch, xR, xC, d1);
                 } else {
-                  xTexelR${_}C${N} = vec4(0.);
+                  xTexelR${_}C${T} = vec4(0.);
                 }
 
                 xCOffset = xC + ${p};
                 if(xCOffset >= 0 && xCOffset < ${i}) {
-                  xTexelR${_}C${N+2} = getX(batch, xR, xCOffset, d1);
+                  xTexelR${_}C${T+2} = getX(batch, xR, xCOffset, d1);
                 } else {
-                  xTexelR${_}C${N+2} = vec4(0.);
+                  xTexelR${_}C${T+2} = vec4(0.);
                 }
 
-                xR${_}C${N} = vec4(
-                  xTexelR${_}C${N}.xy, xTexelR${_}C${N+2}.xy);
-              `,N+1<h&&(x+=`
-                  xR${_}C${N+1} = vec4(
-                    xTexelR${_}C${N}.zw, xTexelR${_}C${N+2}.zw);
-                `)),x+="}");N<h&&(x+=`
-            vec4 wTexelR${_}C${N} = getW(${_}, ${N}, d1, q);
-            wR${_}C${N} = vec4(wTexelR${_}C${N}.xz, wTexelR${_}C${N}.xz);
-          `,N+1<h&&(x+=`
-              vec4 wTexelR${_}C${N+1} = getW(${_}, ${N+1}, d1, q);
-              wR${_}C${N+1} =
-                vec4(wTexelR${_}C${N+1}.xz, wTexelR${_}C${N+1}.xz);`))}for(let _=0;_<d;_++)for(let A=0;A<h;A++)x+=`dotProd += xR${_}C${A} * wR${_}C${A};`;let w="",b="";n&&(o?w=`vec4 activation(vec4 a) {
+                xR${_}C${T} = vec4(
+                  xTexelR${_}C${T}.xy, xTexelR${_}C${T+2}.xy);
+              `,T+1<h&&(x+=`
+                  xR${_}C${T+1} = vec4(
+                    xTexelR${_}C${T}.zw, xTexelR${_}C${T+2}.zw);
+                `)),x+="}");T<h&&(x+=`
+            vec4 wTexelR${_}C${T} = getW(${_}, ${T}, d1, q);
+            wR${_}C${T} = vec4(wTexelR${_}C${T}.xz, wTexelR${_}C${T}.xz);
+          `,T+1<h&&(x+=`
+              vec4 wTexelR${_}C${T+1} = getW(${_}, ${T+1}, d1, q);
+              wR${_}C${T+1} =
+                vec4(wTexelR${_}C${T+1}.xz, wTexelR${_}C${T+1}.xz);`))}for(let _=0;_<d;_++)for(let D=0;D<h;D++)x+=`dotProd += xR${_}C${D} * wR${_}C${D};`;let b="",w="";o&&(n?b=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
-          ${n}
-        }`:s?w=`vec4 activation(vec4 a) {
+          ${o}
+        }`:s?b=`vec4 activation(vec4 a) {
           vec4 b = getLeakyreluAlphaAtOutCoords();
-          ${n}
-        }`:w=`vec4 activation(vec4 x) {
-          ${n}
-        }`,b="result = activation(result);");let k=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
-      ${w}
+          ${o}
+        }`:b=`vec4 activation(vec4 x) {
+          ${o}
+        }`,w="result = activation(result);");let k=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
+      ${b}
 
       const ivec2 strides = ivec2(${c}, ${p});
       const ivec2 pads = ivec2(${l}, ${u});
@@ -2653,10 +2653,10 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
         vec4 result = dotProd;
         ${k}
-        ${b}
+        ${w}
         setOutput(result);
       }
-    `}};function oX(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,filter:s}=e,{strides:a,pad:i,dilations:l,dimRoundingMode:u}=n,c=l;c==null&&(c=[1,1]),y.assert(S.eitherStridesOrDilationsAreOne(a,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${a} and dilations '${c}'`);let p=S.computeConv2DInfo(o.shape,s.shape,a,c,i,u,!0),m;return j().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels==1?m=new Tf(p):m=new Sf(p),t.runWebGLProgram(m,[o,s],"float32")}var bD={kernelName:to,backendName:"webgl",kernelFunc:oX};var wv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,o=e.padInfo.top,s=e.padInfo.left,a=e.outChannels/e.inChannels;this.userCode=`
+    `}};function AX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l,dimRoundingMode:u}=o,c=l;c==null&&(c=[1,1]),y.assert(N.eitherStridesOrDilationsAreOne(a,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${a} and dilations '${c}'`);let p=N.computeConv2DInfo(n.shape,s.shape,a,c,i,u,!0),m;return W().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels==1?m=new Sf(p):m=new Nf(p),t.runWebGLProgram(m,[n,s],"float32")}var Y2={kernelName:tn,backendName:"webgl",kernelFunc:AX};var fv=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,o=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a=e.outChannels/e.inChannels;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2670,14 +2670,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         // 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} - ${o};
+            int xR = wR + yR * ${t} - ${n};
 
             if (xR < 0 || xR >= ${e.inHeight}) {
               continue;
             }
 
             for (int yC = 0; yC < ${e.outWidth}; yC++) {
-              int xC = wC + yC * ${n} - ${s};
+              int xC = wC + yC * ${o} - ${s};
 
               if (xC < 0 || xC >= ${e.inWidth}) {
                 continue;
@@ -2691,7 +2691,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},kv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,o=e.strideHeight,s=e.strideWidth,a=t-1-e.padInfo.top,i=n-1-e.padInfo.left,l=e.outChannels/e.inChannels;this.userCode=`
+    `}},dv=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,o=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=t-1-e.padInfo.top,i=o-1-e.padInfo.left,l=e.outChannels/e.inChannels;this.userCode=`
       const ivec2 pads = ivec2(${a}, ${i});
 
       void main() {
@@ -2705,7 +2705,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         float dotProd = 0.0;
 
         for (int wR = 0; wR < ${t}; wR++) {
-          float dyR = float(dyRCorner + wR) / ${o}.0;
+          float dyR = float(dyRCorner + wR) / ${n}.0;
 
           if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
             continue;
@@ -2714,7 +2714,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
           int wRPerm = ${t} - 1 - wR;
 
-          for (int wC = 0; wC < ${n}; wC++) {
+          for (int wC = 0; wC < ${o}; wC++) {
             float dyC = float(dyCCorner + wC) / ${s}.0;
 
             if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
@@ -2723,7 +2723,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
             }
             int idyC = int(dyC);
 
-            int wCPerm = ${n} - 1 - wC;
+            int wCPerm = ${o} - 1 - wC;
 
             // TO DO: Vec4 over the channelMul
             for (int dm = 0; dm < ${l}; dm++) {
@@ -2736,13 +2736,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function sX(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,dy:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=n,p=S.computeConv2DInfo(o.shape,c,a,i,l,u,!0),m=new wv(p);return t.runWebGLProgram(m,[o,s],"float32")}var wD={kernelName:ql,backendName:"webgl",kernelFunc:sX};function iX(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,filter:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=n,p=S.computeConv2DInfo(c,s.shape,a,i,l,u,!0),m=new kv(p);return t.runWebGLProgram(m,[o,s],"float32")}var kD={kernelName:Kl,backendName:"webgl",kernelFunc:iX};var _v=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
+    `}};function EX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,dy:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=o,p=N.computeConv2DInfo(n.shape,c,a,i,l,u,!0),m=new fv(p);return t.runWebGLProgram(m,[n,s],"float32")}var Z2={kernelName:ql,backendName:"webgl",kernelFunc:EX};function DX(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,filter:s}=e,{strides:a,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=o,p=N.computeConv2DInfo(c,s.shape,a,i,l,u,!0),m=new dv(p);return t.runWebGLProgram(m,[n,s],"float32")}var J2={kernelName:Kl,backendName:"webgl",kernelFunc:DX};var hv=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 aX(r){let{inputs:e,backend:t}=r,{x:n}=e,o=[...n.shape,...n.shape],s=y.sizeFromShape(n.shape),a=pe({inputs:{x:n},backend:t,attrs:{shape:[s]}}),i=new _v(s),l=t.runWebGLProgram(i,[a],a.dtype),u=pe({inputs:{x:l},backend:t,attrs:{shape:o}});return t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(l),u}var _D={kernelName:Xl,backendName:"webgl",kernelFunc:aX};var vv=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:o,strideHeight:s,strideWidth:a,filterHeight:i,filterWidth:l,dilationHeight:u,dilationWidth:c}=e,{top:p,left:m}=o;this.userCode=`
+    `}};function $X(r){let{inputs:e,backend:t}=r,{x:o}=e,n=[...o.shape,...o.shape],s=y.sizeFromShape(o.shape),a=pe({inputs:{x:o},backend:t,attrs:{shape:[s]}}),i=new hv(s),l=t.runWebGLProgram(i,[a],a.dtype),u=pe({inputs:{x:l},backend:t,attrs:{shape:n}});return t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(l),u}var Q2={kernelName:Xl,backendName:"webgl",kernelFunc:$X};var gv=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:o,padInfo:n,strideHeight:s,strideWidth:a,filterHeight:i,filterWidth:l,dilationHeight:u,dilationWidth:c}=e,{top:p,left:m}=n;this.userCode=`
       const ivec2 strides = ivec2(${s}, ${a});
       const ivec2 pads = ivec2(${p}, ${m});
       const float neg_infinity = -3.4e38;
@@ -2764,7 +2764,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
             for (int w = 0; w < ${l}; w++) {
               int wIn = wBeg + w * ${c};
 
-              if (wIn >= 0 && wIn < ${n}) {
+              if (wIn >= 0 && wIn < ${o}) {
                 float xVal = getX(batch, hIn, wIn, d1);
                 float wVal = getW(h, w, d1);
 
@@ -2780,7 +2780,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         float result = curVal;
         setOutput(result);
       }
-    `}};function lX(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,filter:s}=e,{strides:a,pad:i,dilations:l}=n,u=S.computeDilation2DInfo(o.shape,s.shape,a,i,"NHWC",l),c,p=new vv(u);c=t.runWebGLProgram(p,[o,s],"float32");let m=pe({inputs:{x:c},backend:t,attrs:{shape:u.outShape}});return t.disposeIntermediateTensorInfo(c),m}var vD={kernelName:sa,backendName:"webgl",kernelFunc:lX};var uX="return (x >= 0.0) ? x : (exp(x) - 1.0);",cX=`
+    `}};function RX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s}=e,{strides:a,pad:i,dilations:l}=o,u=N.computeDilation2DInfo(n.shape,s.shape,a,i,"NHWC",l),c,p=new gv(u);c=t.runWebGLProgram(p,[n,s],"float32");let m=pe({inputs:{x:c},backend:t,attrs:{shape:u.outShape}});return t.disposeIntermediateTensorInfo(c),m}var eD={kernelName:sa,backendName:"webgl",kernelFunc:RX};var FX="return (x >= 0.0) ? x : (exp(x) - 1.0);",OX=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -2789,27 +2789,27 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,pX=ke({opSnippet:uX,packedOpSnippet:cX}),CD={kernelName:ni,backendName:"webgl",kernelFunc:pX};var mX="return (b >= 1.0) ? a : a * (b + 1.0);",fX=`
+`,PX=ke({opSnippet:FX,packedOpSnippet:OX}),tD={kernelName:oi,backendName:"webgl",kernelFunc:PX};var MX="return (b >= 1.0) ? a : a * (b + 1.0);",LX=`
   vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
   return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
-`,dX=r=>{let{inputs:e,backend:t}=r,{dy:n,y:o}=e,s=j().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ps(fX,n.shape,o.shape):new Xo(mX,n.shape,o.shape);return t.runWebGLProgram(s,[n,o],n.dtype)},ID={kernelName:Yl,backendName:"webgl",kernelFunc:dX};var hX=`
+`,zX=r=>{let{inputs:e,backend:t}=r,{dy:o,y:n}=e,s=W().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ps(LX,o.shape,n.shape):new Xn(MX,o.shape,n.shape);return t.runWebGLProgram(s,[o,n],o.dtype)},rD={kernelName:Yl,backendName:"webgl",kernelFunc:zX};var BX=`
   return vec4(equal(a, b));
-`,gX="return float(a == b);",xX=ot({opSnippet:gX,packedOpSnippet:hX,dtype:"bool"}),ND={kernelName:si,backendName:"webgl",kernelFunc:xX};var yX=`
+`,VX="return float(a == b);",GX=nt({opSnippet:VX,packedOpSnippet:BX,dtype:"bool"}),oD={kernelName:si,backendName:"webgl",kernelFunc:GX};var WX=`
   // Error function is calculated approximately with elementary function.
   // See "Handbook of Mathematical Functions with Formulas,
   // Graphs, and Mathematical Tables", Abramowitz and Stegun.
-  float p = ${S.ERF_P};
-  float a1 = ${S.ERF_A1};
-  float a2 = ${S.ERF_A2};
-  float a3 = ${S.ERF_A3};
-  float a4 = ${S.ERF_A4};
-  float a5 = ${S.ERF_A5};
+  float p = ${N.ERF_P};
+  float a1 = ${N.ERF_A1};
+  float a2 = ${N.ERF_A2};
+  float a3 = ${N.ERF_A3};
+  float a4 = ${N.ERF_A4};
+  float a5 = ${N.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));
-`,bX=ke({opSnippet:yX}),SD={kernelName:oi,backendName:"webgl",kernelFunc:bX};var TD="return exp(x);",Cv=ke({opSnippet:TD,packedOpSnippet:TD,cpuKernelImpl:NE}),AD={kernelName:no,backendName:"webgl",kernelFunc:Cv};function Qg(r){let{inputs:e,attrs:t,backend:n}=r,{dim:o}=t,{input:s}=e,a=s.shape.length,i=s.shape.slice(),l=o;return o<0&&(y.assert(-(a+1)<=o,()=>`Axis must be in the interval [${-(a+1)}, ${a}]`),l=a+o+1),i.splice(l,0,1),pe({inputs:{x:s},backend:n,attrs:{shape:i}})}var ED={kernelName:us,backendName:"webgl",kernelFunc:Qg};var DD="return exp(x) - 1.0;",wX=ke({opSnippet:DD,packedOpSnippet:DD,cpuKernelImpl:SE}),$D={kernelName:ii,backendName:"webgl",kernelFunc:wX};var ex=class{constructor(e,t,n){this.variableNames=["real","imag"];let o=t[1];this.outputShape=t;let s=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=n?`${o}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
+`,jX=ke({opSnippet:WX}),nD={kernelName:ni,backendName:"webgl",kernelFunc:jX};var sD="return exp(x);",xv=ke({opSnippet:sD,packedOpSnippet:sD,cpuKernelImpl:oE}),iD={kernelName:on,backendName:"webgl",kernelFunc:xv};function Yg(r){let{inputs:e,attrs:t,backend:o}=r,{dim:n}=t,{input:s}=e,a=s.shape.length,i=s.shape.slice(),l=n;return n<0&&(y.assert(-(a+1)<=n,()=>`Axis must be in the interval [${-(a+1)}, ${a}]`),l=a+n+1),i.splice(l,0,1),pe({inputs:{x:s},backend:o,attrs:{shape:i}})}var aD={kernelName:us,backendName:"webgl",kernelFunc:Yg};var lD="return exp(x) - 1.0;",UX=ke({opSnippet:lD,packedOpSnippet:lD,cpuKernelImpl:nE}),uD={kernelName:ii,backendName:"webgl",kernelFunc:UX};var Zg=class{constructor(e,t,o){this.variableNames=["real","imag"];let n=t[1];this.outputShape=t;let s=o?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=o?`${n}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
       const float exponentMultiplier = ${s};
 
       float unaryOpComplex(float real, float expR, float imag, float expI) {
@@ -2817,13 +2817,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
       }
 
       float mulMatDFT(int batch, int index) {
-        float indexRatio = float(index) / float(${o});
+        float indexRatio = float(index) / float(${n});
         float exponentMultiplierTimesIndexRatio =
             exponentMultiplier * indexRatio;
 
         float result = 0.0;
 
-        for (int i = 0; i < ${o}; i++) {
+        for (int i = 0; i < ${n}; i++) {
           // x = (-2|2 * PI / N) * index * i;
           float x = exponentMultiplierTimesIndexRatio * float(i);
           float expR = cos(x);
@@ -2842,13 +2842,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         ivec2 coords = getOutputCoords();
         setOutput(mulMatDFT(coords[0], coords[1]));
       }
-    `}};function tx(r,e,t){let n=t.texData.get(r.dataId),o=y.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],a=o/s,i=pe({inputs:{x:r},backend:t,attrs:{shape:[a,s]}}),l=i.shape,u=new ex("real",l,e),c=new ex("imag",l,e),p=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:l},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:l}],m=t.runWebGLProgram(u,p,"float32"),f=t.runWebGLProgram(c,p,"float32"),d=un({inputs:{real:m,imag:f},backend:t});t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f);let h=pe({inputs:{x:d},backend:t,attrs:{shape:r.shape}});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(d),h}function kX(r){let{inputs:e,backend:t}=r,{input:n}=e;return tx(n,!1,t)}var RD={kernelName:Zl,backendName:"webgl",kernelFunc:kX};var Iv=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.outputShape=e,this.userCode=`
+    `}};function Jg(r,e,t){let o=t.texData.get(r.dataId),n=y.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],a=n/s,i=pe({inputs:{x:r},backend:t,attrs:{shape:[a,s]}}),l=i.shape,u=new Zg("real",l,e),c=new Zg("imag",l,e),p=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:l},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:l}],m=t.runWebGLProgram(u,p,"float32"),f=t.runWebGLProgram(c,p,"float32"),d=lo({inputs:{real:m,imag:f},backend:t});t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f);let h=pe({inputs:{x:d},backend:t,attrs:{shape:r.shape}});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(d),h}function HX(r){let{inputs:e,backend:t}=r,{input:o}=e;return Jg(o,!1,t)}var cD={kernelName:Zl,backendName:"webgl",kernelFunc:HX};var yv=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 Af(r){let{backend:e,attrs:t}=r,{shape:n,value:o}=t,{dtype:s}=t;if(s=s||y.inferDtype(o),s==="string"){let a=y.getArrayFromDType(s,y.sizeFromShape(n));return a.fill(o),e.makeTensorInfo(n,s,a)}else{let a=new Iv(n,o),i=a.getCustomSetupFunc(o);return e.runWebGLProgram(a,[],s,i)}}var FD={kernelName:ia,backendName:"webgl",kernelFunc:Af};var Nv=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
+    `}getCustomSetupFunc(e){return(t,o)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(o,"value")),t.gl.uniform1f(this.valueLoc,e)}}};function Tf(r){let{backend:e,attrs:t}=r,{shape:o,value:n}=t,{dtype:s}=t;if(s=s||y.inferDtype(n),s==="string"){let a=y.getArrayFromDType(s,y.sizeFromShape(o));return a.fill(n),e.makeTensorInfo(o,s,a)}else{let a=new yv(o,n),i=a.getCustomSetupFunc(n);return e.runWebGLProgram(a,[],s,i)}}var pD={kernelName:ia,backendName:"webgl",kernelFunc:Tf};var bv=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];
@@ -2862,7 +2862,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
           }
           setOutput(outputValue);
         }
-    `}};var OD={kernelName:ai,backendName:"webgl",kernelFunc:({inputs:r,backend:e})=>{let{image:t}=r,n=e,o=new Nv(t.shape);return n.runWebGLProgram(o,[t],t.dtype)}};var PD="return floor(x);",_X=ke({opSnippet:PD,packedOpSnippet:PD,cpuKernelImpl:TE}),MD={kernelName:oo,backendName:"webgl",kernelFunc:_X};var vX=`
+    `}};var mD={kernelName:ai,backendName:"webgl",kernelFunc:({inputs:r,backend:e})=>{let{image:t}=r,o=e,n=new bv(t.shape);return o.runWebGLProgram(n,[t],t.dtype)}};var fD="return floor(x);",qX=ke({opSnippet:fD,packedOpSnippet:fD,cpuKernelImpl:sE}),dD={kernelName:nn,backendName:"webgl",kernelFunc:qX};var KX=`
   float s = sign(a) * sign(b);
   int ia = round(a);
   int ib = round(b);
@@ -2872,7 +2872,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
   } else {
     return NAN;
   }
-`,CX=`
+`,XX=`
   ivec4 ia = round(a);
   ivec4 ib = round(b);
   bvec4 cond = notEqual(ib, ivec4(0));
@@ -2893,13 +2893,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
     result[3] = idiv(ia[3], ib[3], s[3]);
   }
   return vec4(result);
-`,IX=ot({opSnippet:vX,packedOpSnippet:CX,dtype:"int32"}),LD={kernelName:so,backendName:"webgl",kernelFunc:IX};var Sv=class{constructor(e){this.variableNames=["A"];let t=Ft(),[n,o]=e;this.outputShape=e,this.userCode=`
+`,YX=nt({opSnippet:KX,packedOpSnippet:XX,dtype:"int32"}),hD={kernelName:sn,backendName:"webgl",kernelFunc:YX};var wv=class{constructor(e){this.variableNames=["A"];let t=Rt(),[o,n]=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(${o}.0, ${n}.0);
+        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}.0, ${o}.0);
 
         vec4 values = ${t.texture2D}(A, uv);
         float value;
@@ -2915,7 +2915,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
         setOutput(floor(value * 255.0 + 0.5));
       }
-    `}};var Tv=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=Ft(),[n,o]=e;this.outputShape=e,this.userCode=`
+    `}};var kv=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=Rt(),[o,n]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -2930,7 +2930,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
             depth = coords[2] + col;
 
             vec2 uv = (vec2(texC, texR) + halfCR) /
-                       vec2(${o}.0, ${n}.0);
+                       vec2(${n}.0, ${o}.0);
             vec4 values = ${t.texture2D}(A, uv);
             float value;
             if (depth == 0) {
@@ -2949,8 +2949,8 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
         ${t.output} = result;
       }
-    `}};var zD={kernelName:Mc,backendName:"webgl",kernelFunc:NX},_p;function NX(r){let{inputs:e,backend:t,attrs:n}=r,{pixels:o}=e,{numChannels:s}=n,a=typeof HTMLVideoElement!="undefined"&&o instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&o instanceof HTMLImageElement,[l,u]=a?[o.videoWidth,o.videoHeight]:[o.width,o.height],c=[u,l],p=[u,l,s];(i||a)&&(_p==null&&(_p=document.createElement("canvas").getContext("2d")),_p.canvas.width=l,_p.canvas.height=u,_p.drawImage(o,0,0,l,u),o=_p.canvas);let m=t.makeTensorInfo(c,"int32");t.texData.get(m.dataId).usage=Dr.PIXELS,t.gpgpu.uploadPixelDataToTexture(t.getTexture(m.dataId),o);let f=j().getBool("WEBGL_PACK")?new Tv(p):new Sv(p),d=t.runWebGLProgram(f,[m],"int32");return t.disposeData(m.dataId),d}function SX(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,filter:s,bias:a,preluActivationWeights:i}=e,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:m,activation:f,leakyreluAlpha:d}=n,h=S.convertConv2DDataFormat(c),g=S.computeConv2DInfo(o.shape,s.shape,l,p,u,m,!1,h),x,w=[];if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))x=Yg({x:o,filter:s,convInfo:g,backend:t,bias:a,activation:f,preluActivationWeights:i,leakyreluAlpha:d});else if(j().getBool("WEBGL_CONV_IM2COL")&&o.shape[0]===1)x=Zg({x:o,filter:s,convInfo:g,backend:t,bias:a,activation:f,preluActivationWeights:i,leakyreluAlpha:d});else{let k=a!=null,_=i!=null,A=f==="leakyrelu",N=f?gl(f,!1):null,$=new Nf(g,k,N,_,A),F=[o,s];if(a&&F.push(a),i&&F.push(i),A){let M=t.makeTensorInfo([],"float32",y.createScalarValue(d,"float32"));F.push(M),w.push(M)}x=t.runWebGLProgram($,F,"float32")}let b=pe({inputs:{x},backend:t,attrs:{shape:g.outShape}});return w.push(x),w.forEach(k=>t.disposeIntermediateTensorInfo(k)),b}var BD={kernelName:ks,backendName:"webgl",kernelFunc:SX};function TX(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,filter:s,bias:a,preluActivationWeights:i}=e,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:m,leakyreluAlpha:f}=n,d=[],h=c;h==null&&(h=[1,1]),y.assert(S.eitherStridesOrDilationsAreOne(l,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${h}'`);let g=S.computeConv2DInfo(o.shape,s.shape,l,h,u,p,!0),x=j().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels==1,w=m?gl(m,x):null,b=[o,s],k=a!=null,_=i!=null,A=m==="leakyrelu";if(k&&b.push(a),_&&b.push(i),A){let F=t.makeTensorInfo([],"float32",y.createScalarValue(f,"float32"));b.push(F),d.push(F)}let N;x?N=new Tf(g,k,w,_,A):N=new Sf(g,k,w,_,A);let $=t.runWebGLProgram(N,b,"float32");return d.forEach(F=>t.disposeIntermediateTensorInfo(F)),$}var VD={kernelName:_s,backendName:"webgl",kernelFunc:TX};var Av=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let o=Le(t.length),s=Le(n.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
-        ${o} strides = ${o}(${this.strides});
+    `}};var gD={kernelName:Pc,backendName:"webgl",kernelFunc:ZX},kp;function ZX(r){let{inputs:e,backend:t,attrs:o}=r,{pixels:n}=e,{numChannels:s}=o,a=typeof HTMLVideoElement!="undefined"&&n instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&n instanceof HTMLImageElement,[l,u]=a?[n.videoWidth,n.videoHeight]:[n.width,n.height],c=[u,l],p=[u,l,s];(i||a)&&(kp==null&&(kp=document.createElement("canvas").getContext("2d")),kp.canvas.width=l,kp.canvas.height=u,kp.drawImage(n,0,0,l,u),n=kp.canvas);let m=t.makeTensorInfo(c,"int32");t.texData.get(m.dataId).usage=Dr.PIXELS,t.gpgpu.uploadPixelDataToTexture(t.getTexture(m.dataId),n);let f=W().getBool("WEBGL_PACK")?new kv(p):new wv(p),d=t.runWebGLProgram(f,[m],"int32");return t.disposeData(m.dataId),d}function JX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:m,activation:f,leakyreluAlpha:d}=o,h=N.convertConv2DDataFormat(c),g=N.computeConv2DInfo(n.shape,s.shape,l,p,u,m,!1,h),x,b=[];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"))x=qg({x:n,filter:s,convInfo:g,backend:t,bias:a,activation:f,preluActivationWeights:i,leakyreluAlpha:d});else if(W().getBool("WEBGL_CONV_IM2COL")&&n.shape[0]===1)x=Kg({x:n,filter:s,convInfo:g,backend:t,bias:a,activation:f,preluActivationWeights:i,leakyreluAlpha:d});else{let k=a!=null,_=i!=null,D=f==="leakyrelu",T=f?gl(f,!1):null,R=new If(g,k,T,_,D),O=[n,s];if(a&&O.push(a),i&&O.push(i),D){let M=t.makeTensorInfo([],"float32",y.createScalarValue(d,"float32"));O.push(M),b.push(M)}x=t.runWebGLProgram(R,O,"float32")}let w=pe({inputs:{x},backend:t,attrs:{shape:g.outShape}});return b.push(x),b.forEach(k=>t.disposeIntermediateTensorInfo(k)),w}var xD={kernelName:ks,backendName:"webgl",kernelFunc:JX};function QX(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,filter:s,bias:a,preluActivationWeights:i}=e,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:m,leakyreluAlpha:f}=o,d=[],h=c;h==null&&(h=[1,1]),y.assert(N.eitherStridesOrDilationsAreOne(l,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${h}'`);let g=N.computeConv2DInfo(n.shape,s.shape,l,h,u,p,!0),x=W().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels==1,b=m?gl(m,x):null,w=[n,s],k=a!=null,_=i!=null,D=m==="leakyrelu";if(k&&w.push(a),_&&w.push(i),D){let O=t.makeTensorInfo([],"float32",y.createScalarValue(f,"float32"));w.push(O),d.push(O)}let T;x?T=new Sf(g,k,b,_,D):T=new Nf(g,k,b,_,D);let R=t.runWebGLProgram(T,w,"float32");return d.forEach(O=>t.disposeIntermediateTensorInfo(O)),R}var yD={kernelName:_s,backendName:"webgl",kernelFunc:QX};var _v=class{constructor(e,t,o){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=o;let n=Le(t.length),s=Le(o.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
+        ${n} strides = ${n}(${this.strides});
          void main() {
           ${s} coords = getOutputCoords();
           int flattenIndex = 0;
@@ -2960,21 +2960,21 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
           }
           setOutput(getX(flattenIndex, coords[1]));
         }
-      `}};function AX(r){let{inputs:e,backend:t}=r,{params:n,indices:o}=e,s=o.shape,a=s[s.length-1],[i,l,u,c]=S.prepareAndValidate(n,o),p=pe({inputs:{x:o},backend:t,attrs:{shape:[l,a]}}),m=pe({inputs:{x:n},backend:t,attrs:{shape:[y.sizeFromShape(n.shape)/u,u]}}),f=new Av(a,c,[l,u]),d=t.runWebGLProgram(f,[m,p],m.dtype),h=pe({inputs:{x:d},backend:t,attrs:{shape:i}});return t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(d),h}var GD={kernelName:li,backendName:"webgl",kernelFunc:AX};var Ev=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=Le(this.rank),o=EX(e,2);this.userCode=`
+      `}};function e8(r){let{inputs:e,backend:t}=r,{params:o,indices:n}=e,s=n.shape,a=s[s.length-1],[i,l,u,c]=N.prepareAndValidate(o,n),p=pe({inputs:{x:n},backend:t,attrs:{shape:[l,a]}}),m=pe({inputs:{x:o},backend:t,attrs:{shape:[y.sizeFromShape(o.shape)/u,u]}}),f=new _v(a,c,[l,u]),d=t.runWebGLProgram(f,[m,p],m.dtype),h=pe({inputs:{x:d},backend:t,attrs:{shape:i}});return t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(d),h}var bD={kernelName:li,backendName:"webgl",kernelFunc:e8};var vv=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let o=Le(this.rank),n=t8(e,2);this.userCode=`
       void main() {
-        ${n} resRC = getOutputCoords();
-        setOutput(getA(${o}));
+        ${o} resRC = getOutputCoords();
+        setOutput(getA(${n}));
       }
-    `}};function EX(r,e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let o=0;o<r.length;o++)o===2?n.push("int(getIndices(resRC.x, resRC.z))"):n.push(`${t[o]}`);return n.join()}function DX(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,indices:s}=e,{axis:a,batchDims:i}=n,l=y.parseAxisParam(a,o.shape)[0],u=S.segment_util.collectGatherOpShapeInfo(o,s,l,i),c=y.sizeFromShape(s.shape),p=[],m=pe({inputs:{x:o},backend:t,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),f=pe({inputs:{x:s},backend:t,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(m),p.push(f);let d=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(t.shouldExecuteOnCPU([o,s])||o.dtype==="string"){let w=t.bufferSync(f),b=t.bufferSync(m),k=AE(b,w,d);return p.forEach(_=>t.disposeIntermediateTensorInfo(_)),t.makeTensorInfo(u.outputShape,k.dtype,k.values)}let h=new Ev(m.shape,d),g=t.runWebGLProgram(h,[m,f],m.dtype);p.push(g);let x=pe({inputs:{x:g},backend:t,attrs:{shape:u.outputShape}});return p.forEach(w=>t.disposeIntermediateTensorInfo(w)),x}var WD={kernelName:cs,backendName:"webgl",kernelFunc:DX};var $X="return float(a > b);",RX=`
+    `}};function t8(r,e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[];for(let n=0;n<r.length;n++)n===2?o.push("int(getIndices(resRC.x, resRC.z))"):o.push(`${t[n]}`);return o.join()}function r8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n,indices:s}=e,{axis:a,batchDims:i}=o,l=y.parseAxisParam(a,n.shape)[0],u=N.segment_util.collectGatherOpShapeInfo(n,s,l,i),c=y.sizeFromShape(s.shape),p=[],m=pe({inputs:{x:n},backend:t,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),f=pe({inputs:{x:s},backend:t,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(m),p.push(f);let d=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(t.shouldExecuteOnCPU([n,s])||n.dtype==="string"){let b=t.bufferSync(f),w=t.bufferSync(m),k=iE(w,b,d);return p.forEach(_=>t.disposeIntermediateTensorInfo(_)),t.makeTensorInfo(u.outputShape,k.dtype,k.values)}let h=new vv(m.shape,d),g=t.runWebGLProgram(h,[m,f],m.dtype);p.push(g);let x=pe({inputs:{x:g},backend:t,attrs:{shape:u.outputShape}});return p.forEach(b=>t.disposeIntermediateTensorInfo(b)),x}var wD={kernelName:cs,backendName:"webgl",kernelFunc:r8};var o8="return float(a > b);",n8=`
   return vec4(greaterThan(a, b));
-`,FX=ot({opSnippet:$X,packedOpSnippet:RX,cpuKernelImpl:EE,dtype:"bool"}),jD={kernelName:ui,backendName:"webgl",kernelFunc:FX};var OX="return float(a >= b);",PX=`
+`,s8=nt({opSnippet:o8,packedOpSnippet:n8,cpuKernelImpl:aE,dtype:"bool"}),kD={kernelName:ui,backendName:"webgl",kernelFunc:s8};var i8="return float(a >= b);",a8=`
   return vec4(greaterThanEqual(a, b));
-`,MX=ot({opSnippet:OX,packedOpSnippet:PX,dtype:"bool"}),UD={kernelName:ao,backendName:"webgl",kernelFunc:MX};function LX(r){let{inputs:e,backend:t}=r,{input:n}=e;return tx(n,!0,t)}var HD={kernelName:Jl,backendName:"webgl",kernelFunc:LX};var zX="return float(!isnan(x) && !isinf(x));",BX=ke({opSnippet:zX,dtype:"bool"}),qD={kernelName:ci,backendName:"webgl",kernelFunc:BX};var VX="return float(isinf(x));",GX=ke({opSnippet:VX,dtype:"bool"}),KD={kernelName:pi,backendName:"webgl",kernelFunc:GX};var WX="return float(isnan(x));",jX=ke({opSnippet:WX,dtype:"bool"}),XD={kernelName:mi,backendName:"webgl",kernelFunc:jX};var UX="return float(a < b);",HX=`
+`,l8=nt({opSnippet:i8,packedOpSnippet:a8,dtype:"bool"}),_D={kernelName:ln,backendName:"webgl",kernelFunc:l8};function u8(r){let{inputs:e,backend:t}=r,{input:o}=e;return Jg(o,!0,t)}var vD={kernelName:Jl,backendName:"webgl",kernelFunc:u8};var c8="return float(!isnan(x) && !isinf(x));",p8=ke({opSnippet:c8,dtype:"bool"}),CD={kernelName:ci,backendName:"webgl",kernelFunc:p8};var m8="return float(isinf(x));",f8=ke({opSnippet:m8,dtype:"bool"}),ID={kernelName:pi,backendName:"webgl",kernelFunc:f8};var d8="return float(isnan(x));",h8=ke({opSnippet:d8,dtype:"bool"}),ND={kernelName:mi,backendName:"webgl",kernelFunc:h8};var g8="return float(a < b);",x8=`
   return vec4(lessThan(a, b));
-`,qX=ot({opSnippet:UX,packedOpSnippet:HX,cpuKernelImpl:DE,dtype:"bool"}),YD={kernelName:fi,backendName:"webgl",kernelFunc:qX};var KX="return float(a <= b);",XX=`
+`,y8=nt({opSnippet:g8,packedOpSnippet:x8,cpuKernelImpl:lE,dtype:"bool"}),SD={kernelName:fi,backendName:"webgl",kernelFunc:y8};var b8="return float(a <= b);",w8=`
   return vec4(lessThanEqual(a, b));
-`,YX=ot({opSnippet:KX,packedOpSnippet:XX,dtype:"bool"}),ZD={kernelName:di,backendName:"webgl",kernelFunc:YX};function ZX(r){let{backend:e,attrs:t}=r,{start:n,stop:o,num:s}=t,a=$E(n,o,s);return e.makeTensorInfo([a.length],"float32",a)}var JD={kernelName:eu,backendName:"webgl",kernelFunc:ZX};var JX=`if (x < 0.0) return NAN;
-  return log(x);`,QX=`
+`,k8=nt({opSnippet:b8,packedOpSnippet:w8,dtype:"bool"}),TD={kernelName:di,backendName:"webgl",kernelFunc:k8};function _8(r){let{backend:e,attrs:t}=r,{start:o,stop:n,num:s}=t,a=uE(o,n,s);return e.makeTensorInfo([a.length],"float32",a)}var AD={kernelName:eu,backendName:"webgl",kernelFunc:_8};var v8=`if (x < 0.0) return NAN;
+  return log(x);`,C8=`
   vec4 result = log(x);
   vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
   result.r = isNaN.r == 1.0 ? NAN : result.r;
@@ -2983,16 +2983,16 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
   result.a = isNaN.a == 1.0 ? NAN : result.a;
 
   return result;
-`,e7=ke({opSnippet:JX,packedOpSnippet:QX,cpuKernelImpl:RE}),QD={kernelName:uo,backendName:"webgl",kernelFunc:e7};var t7="return log(1.0 + x);",r7=ke({opSnippet:t7}),e$={kernelName:hi,backendName:"webgl",kernelFunc:r7};var n7="return float(a >= 1.0 && b >= 1.0);",o7=`
+`,I8=ke({opSnippet:v8,packedOpSnippet:C8,cpuKernelImpl:cE}),ED={kernelName:cn,backendName:"webgl",kernelFunc:I8};var N8="return log(1.0 + x);",S8=ke({opSnippet:N8}),DD={kernelName:hi,backendName:"webgl",kernelFunc:S8};var T8="return float(a >= 1.0 && b >= 1.0);",A8=`
   return vec4(
     vec4(greaterThanEqual(a, vec4(1.0))) *
     vec4(greaterThanEqual(b, vec4(1.0))));
-`,s7=ot({opSnippet:n7,packedOpSnippet:o7,dtype:"bool"}),t$={kernelName:gi,backendName:"webgl",kernelFunc:s7};var i7="return float(!(x >= 1.0));",a7=ke({opSnippet:i7}),r$={kernelName:Ja,backendName:"webgl",kernelFunc:a7};var l7="return float(a >= 1.0 || b >= 1.0);",u7=`
+`,E8=nt({opSnippet:T8,packedOpSnippet:A8,dtype:"bool"}),$D={kernelName:gi,backendName:"webgl",kernelFunc:E8};var D8="return float(!(x >= 1.0));",$8=ke({opSnippet:D8}),RD={kernelName:Ja,backendName:"webgl",kernelFunc:$8};var R8="return float(a >= 1.0 || b >= 1.0);",F8=`
   return min(
     vec4(greaterThanEqual(a, vec4(1.0))) +
     vec4(greaterThanEqual(b, vec4(1.0))),
     vec4(1.0));
-`,c7=ot({opSnippet:l7,packedOpSnippet:u7,dtype:"bool"}),n$={kernelName:Qa,backendName:"webgl",kernelFunc:c7};var Dv=class{constructor(e,t,n,o,s){this.variableNames=["x"],this.outputShape=[];let a=t,i=e[3]-1;this.outputShape=e;let l,u=`float(${n}) + float(${o}) * sum`;s===.5?l=`inversesqrt(${u})`:s===1?l=`1.0/(${u})`:l=`exp(log(${u}) * float(-${s}));`,this.userCode=`
+`,O8=nt({opSnippet:R8,packedOpSnippet:F8,dtype:"bool"}),FD={kernelName:Qa,backendName:"webgl",kernelFunc:O8};var Cv=class{constructor(e,t,o,n,s){this.variableNames=["x"],this.outputShape=[];let a=t,i=e[3]-1;this.outputShape=e;let l,u=`float(${o}) + float(${n}) * sum`;s===.5?l=`inversesqrt(${u})`:s===1?l=`1.0/(${u})`:l=`exp(log(${u}) * float(-${s}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3011,7 +3011,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         float val = x * ${l};
         setOutput(val);
       }
-    `}};var $v=class{constructor(e,t,n,o,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,i=e[3]-1;this.outputShape=e;let l,u=`float(${n}) + float(${o}) * sum`;s===.5?l=`inversesqrt(${u})`:s===1?l=`1.0/(${u})`:l=`exp(log(${u}) * float(-${s}));`,this.userCode=`
+    `}};var Iv=class{constructor(e,t,o,n,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,i=e[3]-1;this.outputShape=e;let l,u=`float(${o}) + float(${n}) * sum`;s===.5?l=`inversesqrt(${u})`:s===1?l=`1.0/(${u})`:l=`exp(log(${u}) * float(-${s}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords.x;
@@ -3073,7 +3073,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         vec4 result = xAtOutputCoords * ${l};
         setOutput(result);
       }
-    `}};var p7=r=>{let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{depthRadius:s,bias:a,alpha:i,beta:l}=n,u=j().getBool("WEBGL_PACK_NORMALIZATION")?new $v(o.shape,s,a,i,l):new Dv(o.shape,s,a,i,l);return t.runWebGLProgram(u,[o],o.dtype)},o$={kernelName:aa,backendName:"webgl",kernelFunc:p7};var Rv=class{constructor(e,t,n,o,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=o,this.beta=s,this.userCode=`
+    `}};var P8=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{depthRadius:s,bias:a,alpha:i,beta:l}=o,u=W().getBool("WEBGL_PACK_NORMALIZATION")?new Iv(n.shape,s,a,i,l):new Cv(n.shape,s,a,i,l);return t.runWebGLProgram(u,[n],n.dtype)},OD={kernelName:aa,backendName:"webgl",kernelFunc:P8};var Nv=class{constructor(e,t,o,n,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=o,this.alpha=n,this.beta=s,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3102,14 +3102,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
             }
           }
 
-          norm = float(${o}) * norm + float(${n});
+          norm = float(${n}) * norm + float(${o});
 
           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(${o})
+              float dyi = -2.0 * float(${n})
                 * float(${s})
                 * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
                 / norm;
@@ -3128,14 +3128,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
       }
       setOutput(result);
       }
-    `}};var m7=r=>{let{inputs:e,backend:t,attrs:n}=r,{x:o,y:s,dy:a}=e,{depthRadius:i,bias:l,alpha:u,beta:c}=n,p=new Rv(o.shape,i,l,u,c);return t.runWebGLProgram(p,[o,s,a],o.dtype)},s$={kernelName:tu,backendName:"webgl",kernelFunc:m7};function i$(r,e,t,n){let o=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/o,i=pe({inputs:{x:r},attrs:{shape:[a,o]},backend:n}),l=Nn(i,r.dtype,"max",n),u=pe({inputs:{x:l},attrs:{shape:t},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}function Fv(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{reductionIndices:s,keepDims:a}=n,i=o.shape.length,l=y.parseAxisParam(s,o.shape),u=l,c=S.getAxesPermutation(u,i),p=c!=null,m=t.shouldExecuteOnCPU([o]),f=o;if(p){if(m){let b=t.texData.get(f.dataId).values,k=new Array(i);for(let N=0;N<k.length;N++)k[N]=o.shape[c[N]];let _=kp(b,o.shape,o.dtype,c,k);f=t.makeTensorInfo(k,o.dtype);let A=t.texData.get(f.dataId);A.values=_}else f=xl(o,c,t);u=S.getInnerMostAxes(u.length,i)}S.assertAxesAreInnerMostDims("max",u,i);let[d,h]=S.computeOutAndReduceShapes(f.shape,u),g=d;a&&(g=S.expandShapeToKeepDim(d,l));let x;if(m){let b=t.texData.get(f.dataId).values,k=FE(b,y.sizeFromShape(h),g,o.dtype);x=t.makeTensorInfo(g,o.dtype);let _=t.texData.get(x.dataId);_.values=k}else x=i$(f,h,g,t);return p&&t.disposeIntermediateTensorInfo(f),x}var a$={kernelName:co,backendName:"webgl",kernelFunc:Fv};var f7=Wg+`
+    `}};var M8=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n,y:s,dy:a}=e,{depthRadius:i,bias:l,alpha:u,beta:c}=o,p=new Nv(n.shape,i,l,u,c);return t.runWebGLProgram(p,[n,s,a],n.dtype)},PD={kernelName:tu,backendName:"webgl",kernelFunc:M8};function MD(r,e,t,o){let n=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/n,i=pe({inputs:{x:r},attrs:{shape:[a,n]},backend:o}),l=No(i,r.dtype,"max",o),u=pe({inputs:{x:l},attrs:{shape:t},backend:o});return o.disposeIntermediateTensorInfo(i),o.disposeIntermediateTensorInfo(l),u}function Sv(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{reductionIndices:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=c!=null,m=t.shouldExecuteOnCPU([n]),f=n;if(p){if(m){let w=t.texData.get(f.dataId).values,k=new Array(i);for(let T=0;T<k.length;T++)k[T]=n.shape[c[T]];let _=wp(w,n.shape,n.dtype,c,k);f=t.makeTensorInfo(k,n.dtype);let D=t.texData.get(f.dataId);D.values=_}else f=xl(n,c,t);u=N.getInnerMostAxes(u.length,i)}N.assertAxesAreInnerMostDims("max",u,i);let[d,h]=N.computeOutAndReduceShapes(f.shape,u),g=d;a&&(g=N.expandShapeToKeepDim(d,l));let x;if(m){let w=t.texData.get(f.dataId).values,k=pE(w,y.sizeFromShape(h),g,n.dtype);x=t.makeTensorInfo(g,n.dtype);let _=t.texData.get(x.dataId);_.values=k}else x=MD(f,h,g,t);return p&&t.disposeIntermediateTensorInfo(f),x}var LD={kernelName:pn,backendName:"webgl",kernelFunc:Sv};var L8=Bg+`
   return max(a, b);
-`,d7=`
+`,z8=`
   vec4 result = vec4(max(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
   `+hl+`
   return result;
-`,h7=ot({opSnippet:f7,packedOpSnippet:d7,cpuKernelImpl:OE}),l$={kernelName:po,backendName:"webgl",kernelFunc:h7};function g7(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e;Rs(o,"maxPool");let{filterSize:s,strides:a,pad:i,dimRoundingMode:l}=n,u=1;y.assert(S.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=S.computePool2DInfo(o.shape,s,a,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return Ut({inputs:{x:o},backend:t});let p=new Vi(c,"max",!1);return t.runWebGLProgram(p,[o],o.dtype)}var u$={kernelName:mo,backendName:"webgl",kernelFunc:g7};function x7(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{filterSize:s,strides:a,pad:i,dataFormat:l,dimRoundingMode:u}=n,c=[1,1,1],p=S.computePool3DInfo(o.shape,s,a,c,i,u,l),m=new ec(p,"max",!1);return t.runWebGLProgram(m,[o],o.dtype)}var c$={kernelName:la,backendName:"webgl",kernelFunc:x7};var Ov=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,o=e.dilationHeight,s=e.effectiveFilterHeight,a=e.effectiveFilterWidth,i=s-1-e.padInfo.top,l=a-1-e.padInfo.left,u=s*a-1;this.userCode=`
+`,B8=nt({opSnippet:L8,packedOpSnippet:z8,cpuKernelImpl:mE}),zD={kernelName:mn,backendName:"webgl",kernelFunc:B8};function V8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e;Rs(n,"maxPool");let{filterSize:s,strides:a,pad:i,dimRoundingMode:l}=o,u=1;y.assert(N.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=N.computePool2DInfo(n.shape,s,a,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&y.arraysEqual(c.inShape,c.outShape))return jt({inputs:{x:n},backend:t});let p=new Vi(c,"max",!1);return t.runWebGLProgram(p,[n],n.dtype)}var BD={kernelName:fn,backendName:"webgl",kernelFunc:V8};function G8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{filterSize:s,strides:a,pad:i,dataFormat:l,dimRoundingMode:u}=o,c=[1,1,1],p=N.computePool3DInfo(n.shape,s,a,c,i,u,l),m=new Qu(p,"max",!1);return t.runWebGLProgram(m,[n],n.dtype)}var VD={kernelName:la,backendName:"webgl",kernelFunc:G8};var Tv=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,o=e.strideWidth,n=e.dilationHeight,s=e.effectiveFilterHeight,a=e.effectiveFilterWidth,i=s-1-e.padInfo.top,l=a-1-e.padInfo.left,u=s*a-1;this.userCode=`
       const ivec2 pads = ivec2(${i}, ${l});
 
       void main() {
@@ -3151,7 +3151,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         // ? = to be determined. : = across all values in that axis.
         float dotProd = 0.0;
         for (int wR = 0; wR < ${s};
-          wR += ${o}) {
+          wR += ${n}) {
           float dyR = float(dyRCorner + wR) / ${t}.0;
 
           if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
@@ -3160,7 +3160,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
           int idyR = int(dyR);
 
           for (int wC = 0; wC < ${a}; wC++) {
-            float dyC = float(dyCCorner + wC) / ${n}.0;
+            float dyC = float(dyCCorner + wC) / ${o}.0;
 
             if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                 fract(dyC) > 0.0) {
@@ -3181,7 +3181,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}},Pv=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,o=e.strideWidth,s=e.dilationDepth,a=e.dilationHeight,i=e.dilationWidth,l=e.effectiveFilterDepth,u=e.effectiveFilterHeight,c=e.effectiveFilterWidth,p=l-1-e.padInfo.front,m=u-1-e.padInfo.top,f=c-1-e.padInfo.left,d=l*u*c-1;this.userCode=`
+    `}},Av=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,o=e.strideHeight,n=e.strideWidth,s=e.dilationDepth,a=e.dilationHeight,i=e.dilationWidth,l=e.effectiveFilterDepth,u=e.effectiveFilterHeight,c=e.effectiveFilterWidth,p=l-1-e.padInfo.front,m=u-1-e.padInfo.top,f=c-1-e.padInfo.left,d=l*u*c-1;this.userCode=`
       const ivec3 pads = ivec3(${p}, ${m}, ${f});
 
       void main() {
@@ -3210,7 +3210,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
           for (int wR = 0; wR < ${u};
               wR += ${a}) {
-            float dyR = float(dyRCorner + wR) / ${n}.0;
+            float dyR = float(dyRCorner + wR) / ${o}.0;
 
             if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
                 fract(dyR) > 0.0) {
@@ -3220,7 +3220,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
             for (int wC = 0; wC < ${c};
                 wC += ${i}) {
-              float dyC = float(dyCCorner + wC) / ${o}.0;
+              float dyC = float(dyCCorner + wC) / ${n}.0;
 
               if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
                   fract(dyC) > 0.0) {
@@ -3245,14 +3245,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         }
         setOutput(dotProd);
       }
-    `}};function y7(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,input:s}=e,a=s,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=n,p=[1,1,1],m=S.computePool3DInfo(a.shape,i,l,p,u,c),f=new ec(m,"max",!0),d=t.runWebGLProgram(f,[a],a.dtype),h=new Pv(m),g=t.runWebGLProgram(h,[o,d],a.dtype);return t.disposeIntermediateTensorInfo(d),g}var p$={kernelName:nu,backendName:"webgl",kernelFunc:y7};function b7(r){let{inputs:e,backend:t,attrs:n}=r,{dy:o,input:s,output:a}=e,i=s;Rs([s,a],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=n,m=S.computePool2DInfo(i.shape,l,u,1,c,p),f=!0,d=new Vi(m,"max",f),h=t.runWebGLProgram(d,[i],i.dtype),g=new Ov(m),x=t.runWebGLProgram(g,[o,h],i.dtype);return t.disposeIntermediateTensorInfo(h),x}var m$={kernelName:ru,backendName:"webgl",kernelFunc:b7};function f$(r,e,t,n){let o=new Vi(t,"max",!1),s=n.runWebGLProgram(o,[r],"float32");o=new Vi(t,"max",!0,!0,e);let a=n.runWebGLProgram(o,[r],"float32");return[s,a]}var d$={kernelName:ou,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:n}=r,{filterSize:o,strides:s,pad:a,includeBatchInIndex:i}=e,l=t;y.assert(n.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let u=[1,1];y.assert(S.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=S.computePool2DInfo(n.shape,o,s,u,a),[p,m]=f$(n,i,c,l);return[p,m]}};function h$(r,e,t,n){let o=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/o,i=pe({inputs:{x:r},attrs:{shape:[a,o]},backend:n}),l=Nn(i,"float32","mean",n),u=pe({inputs:{x:l},attrs:{shape:t},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var g$={kernelName:fo,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:n}=r,{keepDims:o,axis:s}=e,a=t,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=S.getAxesPermutation(u,i),p=c!=null,m=a.shouldExecuteOnCPU([n]),f=[],d=n;if(p){if(m){let k=a.texData.get(d.dataId).values,_=new Array(i);for(let $=0;$<_.length;$++)_[$]=n.shape[c[$]];let A=kp(k,n.shape,n.dtype,c,_);d=a.makeTensorInfo(_,n.dtype);let N=a.texData.get(d.dataId);N.values=A}else d=xl(n,c,a);f.push(d),u=S.getInnerMostAxes(u.length,i)}S.assertAxesAreInnerMostDims("sum",u,i);let[h,g]=S.computeOutAndReduceShapes(d.shape,u),x=h;o&&(x=S.expandShapeToKeepDim(h,l));let w=h$(d,g,x,a);for(let b of f)a.disposeIntermediateTensorInfo(b);return w}};function w7(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{axis:s,keepDims:a}=n,i=o.shape.length,l=y.parseAxisParam(s,o.shape),u=l,c=S.getAxesPermutation(u,i),p=o;c!=null&&(p=Lt({inputs:{x:o},backend:t,attrs:{perm:c}}),u=S.getInnerMostAxes(u.length,o.shape.length)),S.assertAxesAreInnerMostDims("min",u,i);let[m,f]=S.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=Nn(h,h.dtype,"min",t),x;if(a){let w=S.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:w}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var x$={kernelName:ho,backendName:"webgl",kernelFunc:w7};var k7=Wg+`
+    `}};function W8(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s}=e,a=s,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=o,p=[1,1,1],m=N.computePool3DInfo(a.shape,i,l,p,u,c),f=new Qu(m,"max",!0),d=t.runWebGLProgram(f,[a],a.dtype),h=new Av(m),g=t.runWebGLProgram(h,[n,d],a.dtype);return t.disposeIntermediateTensorInfo(d),g}var GD={kernelName:ou,backendName:"webgl",kernelFunc:W8};function j8(r){let{inputs:e,backend:t,attrs:o}=r,{dy:n,input:s,output:a}=e,i=s;Rs([s,a],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=o,m=N.computePool2DInfo(i.shape,l,u,1,c,p),f=!0,d=new Vi(m,"max",f),h=t.runWebGLProgram(d,[i],i.dtype),g=new Tv(m),x=t.runWebGLProgram(g,[n,h],i.dtype);return t.disposeIntermediateTensorInfo(h),x}var WD={kernelName:ru,backendName:"webgl",kernelFunc:j8};function jD(r,e,t,o){let n=new Vi(t,"max",!1),s=o.runWebGLProgram(n,[r],"float32");n=new Vi(t,"max",!0,!0,e);let a=o.runWebGLProgram(n,[r],"float32");return[s,a]}var UD={kernelName:nu,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o}=r,{filterSize:n,strides:s,pad:a,includeBatchInIndex:i}=e,l=t;y.assert(o.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${o.shape.length}.`);let u=[1,1];y.assert(N.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=N.computePool2DInfo(o.shape,n,s,u,a),[p,m]=jD(o,i,c,l);return[p,m]}};function HD(r,e,t,o){let n=y.sizeFromShape(e),a=y.sizeFromShape(r.shape)/n,i=pe({inputs:{x:r},attrs:{shape:[a,n]},backend:o}),l=No(i,"float32","mean",o),u=pe({inputs:{x:l},attrs:{shape:t},backend:o});return o.disposeIntermediateTensorInfo(i),o.disposeIntermediateTensorInfo(l),u}var qD={kernelName:dn,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{x:o}=r,{keepDims:n,axis:s}=e,a=t,i=o.shape.length,l=y.parseAxisParam(s,o.shape),u=l,c=N.getAxesPermutation(u,i),p=c!=null,m=a.shouldExecuteOnCPU([o]),f=[],d=o;if(p){if(m){let k=a.texData.get(d.dataId).values,_=new Array(i);for(let R=0;R<_.length;R++)_[R]=o.shape[c[R]];let D=wp(k,o.shape,o.dtype,c,_);d=a.makeTensorInfo(_,o.dtype);let T=a.texData.get(d.dataId);T.values=D}else d=xl(o,c,a);f.push(d),u=N.getInnerMostAxes(u.length,i)}N.assertAxesAreInnerMostDims("sum",u,i);let[h,g]=N.computeOutAndReduceShapes(d.shape,u),x=h;n&&(x=N.expandShapeToKeepDim(h,l));let b=HD(d,g,x,a);for(let w of f)a.disposeIntermediateTensorInfo(w);return b}};function U8(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=y.parseAxisParam(s,n.shape),u=l,c=N.getAxesPermutation(u,i),p=n;c!=null&&(p=Mt({inputs:{x:n},backend:t,attrs:{perm:c}}),u=N.getInnerMostAxes(u.length,n.shape.length)),N.assertAxesAreInnerMostDims("min",u,i);let[m,f]=N.computeOutAndReduceShapes(p.shape,u),d=y.sizeFromShape(f),h=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,d]}}),g=No(h,h.dtype,"min",t),x;if(a){let b=N.expandShapeToKeepDim(m,l);x=pe({inputs:{x:g},backend:t,attrs:{shape:b}})}else x=pe({inputs:{x:g},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(h),t.disposeIntermediateTensorInfo(g),c!=null&&t.disposeIntermediateTensorInfo(p),x}var KD={kernelName:hn,backendName:"webgl",kernelFunc:U8};var H8=Bg+`
   return min(a, b);
-`,_7=`
+`,q8=`
   vec4 result = vec4(min(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
   `+hl+`
   return result;
-`,v7=ot({opSnippet:k7,packedOpSnippet:_7,cpuKernelImpl:PE}),y$={kernelName:go,backendName:"webgl",kernelFunc:v7};var Mv=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((c,p)=>c[0]+e[p]+c[1]);let o=e.length,s=Le(o),a=t.map(c=>c[0]).join(","),i=t.map((c,p)=>c[0]+e[p]).join(","),l=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,o),u=n==="reflect"?0:1;if(o===1){this.userCode=`
+`,K8=nt({opSnippet:H8,packedOpSnippet:q8,cpuKernelImpl:fE}),XD={kernelName:gn,backendName:"webgl",kernelFunc:K8};var Ev=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=t.map((c,p)=>c[0]+e[p]+c[1]);let n=e.length,s=Le(n),a=t.map(c=>c[0]).join(","),i=t.map((c,p)=>c[0]+e[p]).join(","),l=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),u=o==="reflect"?0:1;if(n===1){this.userCode=`
         int start = ${a};
         int end = ${i};
 
@@ -3271,7 +3271,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
 
       void main() {
         ${s} outC = getOutputCoords();
-        for (int i = 0; i < ${o}; i++) {
+        for (int i = 0; i < ${n}; i++) {
           if (outC[i] < start[i]) {
             outC[i] = start[i] * 2 - outC[i] - ${u};
           } else if(outC[i] >= end[i]) {
@@ -3281,7 +3281,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         ${s} coords = outC - start;
         setOutput(getX(${l}));
       }
-    `}};var Lv=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((d,h)=>d[0]+e[h]+d[1]);let o=e.length,s=Le(o),a=t.map(d=>d[0]).join(","),i=t.map((d,h)=>d[0]+e[h]).join(","),l=jt("rc",o),u=jt("source",o),c=`${l[o-1]} < ${this.outputShape[o-1]}`,p=o===1?"source":`vec2(${u.slice(-2).join()})`,m=n==="reflect"?0:1,f="";if(o===1){let d=`
+    `}};var Dv=class{constructor(e,t,o){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((d,h)=>d[0]+e[h]+d[1]);let n=e.length,s=Le(n),a=t.map(d=>d[0]).join(","),i=t.map((d,h)=>d[0]+e[h]).join(","),l=Wt("rc",n),u=Wt("source",n),c=`${l[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${u.slice(-2).join()})`,m=o==="reflect"?0:1,f="";if(n===1){let d=`
         ${s} source = rc;
         if (source < start) {
           source = start * 2 - source - ${m};
@@ -3293,7 +3293,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         ${s} rc = outputLoc;
         ${d}
         result[0] = getChannel(getX(${u.join()}), ${p});
-        ${l[o-1]} += 1;
+        ${l[n-1]} += 1;
         if(${c}) {
           ${d}
           result[1] = getChannel(getX(${u.join()}), ${p});
@@ -3311,17 +3311,17 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         ${s} rc = outputLoc;
         ${d}
         result[0] = getChannel(getX(${u.join()}), ${p});
-        ${l[o-1]} += 1;
+        ${l[n-1]} += 1;
         if(${c}) {
           ${d}
           result[1] = getChannel(getX(${u.join()}), ${p});
         }
         rc = outputLoc;
-        ${l[o-2]} += 1;
-        if(${l[o-2]} < ${this.outputShape[o-2]}) {
+        ${l[n-2]} += 1;
+        if(${l[n-2]} < ${this.outputShape[n-2]}) {
           ${d}
           result[2] = getChannel(getX(${u.join()}), ${p});
-          ${l[o-1]} += 1;
+          ${l[n-1]} += 1;
           if(${c}) {
             ${d}
             result[3] = getChannel(getX(${u.join()}), ${p});
@@ -3337,13 +3337,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         ${f}
         setOutput(result);
       }
-    `}};var C7=({inputs:r,backend:e,attrs:t})=>{let{x:n}=r,{paddings:o,mode:s}=t,a=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Lv(n.shape,o,s):new Mv(n.shape,o,s);return e.runWebGLProgram(a,[n],n.dtype)},b$={kernelName:ua,backendName:"webgl",kernelFunc:C7};var I7=`if (b == 0.0) return NAN;
-  return mod(a, b);`,N7=`
+    `}};var X8=({inputs:r,backend:e,attrs:t})=>{let{x:o}=r,{paddings:n,mode:s}=t,a=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Dv(o.shape,n,s):new Ev(o.shape,n,s);return e.runWebGLProgram(a,[o],o.dtype)},YD={kernelName:ua,backendName:"webgl",kernelFunc:X8};var Y8=`if (b == 0.0) return NAN;
+  return mod(a, b);`,Z8=`
   vec4 result = mod(a, b);
   vec4 isNaN = vec4(equal(b, vec4(0.0)));
   `+hl+`
   return result;
-`,S7=ot({opSnippet:I7,packedOpSnippet:N7}),w$={kernelName:xi,backendName:"webgl",kernelFunc:S7};var zv=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=`
+`,J8=nt({opSnippet:Y8,packedOpSnippet:Z8}),ZD={kernelName:xi,backendName:"webgl",kernelFunc:J8};var $v=class{constructor(e,t,o){this.variableNames=["probs"],this.outputShape=[e,o],this.userCode=`
       uniform float seed;
 
       void main() {
@@ -3365,11 +3365,11 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,T8=ke({opSnippet:S8}),M2={kernelNam
         // 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)}}};var T7=`
+    `}getCustomSetupFunc(e){return(t,o)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(o,"seed")),t.gl.uniform1f(this.seedLoc,e)}}};var Q8=`
 if (a == b) {
   return 1.0;
 };
-return a / b;`,A7=`
+return a / b;`,eY=`
   // vec4 one = vec4(equal(a, b));
   // return one + (vec4(1.0) - one) * a / b;
   vec4 result = a / b;
@@ -3387,14 +3387,14 @@ return a / b;`,A7=`
   }
 
   return result;
-`,Bv=ot({opSnippet:T7,packedOpSnippet:A7,checkOutOfBounds:!0}),k$={kernelName:ro,backendName:"webgl",kernelFunc:Bv};var _$="return a - b;",Vv=ot({opSnippet:_$,packedOpSnippet:_$,supportsComplex:!0,cpuKernelImpl:jE}),v$={kernelName:Fo,backendName:"webgl",kernelFunc:Vv};function Gv(r){let{inputs:e,backend:t,attrs:n}=r,{logits:o}=e,{dim:s}=n,a=y.parseAxisParam([s],o.shape),i=Fv({inputs:{x:o},backend:t,attrs:{reductionIndices:a,keepDims:!1}}),l=S.expandShapeToKeepDim(i.shape,a),u=pe({inputs:{x:i},backend:t,attrs:{shape:l}}),c=Vv({inputs:{a:o,b:u},backend:t}),p=Cv({inputs:{x:c},backend:t}),m=If({inputs:{x:p},backend:t,attrs:{axis:a,keepDims:!1}}),f=pe({inputs:{x:m},backend:t,attrs:{shape:l}}),d=Bv({inputs:{a:p,b:f},backend:t});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(u),t.disposeIntermediateTensorInfo(c),t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f),d}var C$={kernelName:$o,backendName:"webgl",kernelFunc:Gv};function E7(r){let{inputs:e,backend:t,attrs:n}=r,{logits:o}=e,{numSamples:s,seed:a,normalized:i}=n,l=i?o:Gv({inputs:{logits:o},backend:t,attrs:{dim:o.shape.length-1}}),u=l.shape[0],c=l.shape[1],p=new zv(u,c,s),m=p.getCustomSetupFunc(a),f=t.runWebGLProgram(p,[l],"int32",m);return i||t.disposeIntermediateTensorInfo(l),f}var I$={kernelName:su,backendName:"webgl",kernelFunc:E7};var N$="return -x;";function D7(r){let{inputs:e,backend:t}=r,{x:n}=e;if(t.shouldExecuteOnCPU([n])){let s=t.texData.get(n.dataId),[a,i]=LE(s.values,n.shape,n.dtype);return t.makeTensorInfo(i,n.dtype,a)}let o;return j().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new Os(n.shape,N$):o=new ln(n.shape,N$),t.runWebGLProgram(o,[n],n.dtype)}var S$={kernelName:ps,backendName:"webgl",kernelFunc:D7};var $7=Ar.nonMaxSuppressionV3Impl;function R7(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:n}=r,{boxes:o,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l}=n,u=t.readSync(o.dataId),c=t.readSync(s.dataId),{selectedIndices:p}=$7(u,c,a,i,l);return t.makeTensorInfo([p.length],"int32",new Int32Array(p))}var T$={kernelName:bi,backendName:"webgl",kernelFunc:R7};var F7=Ar.nonMaxSuppressionV4Impl;function O7(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:n}=r,{boxes:o,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=n,c=t.readSync(o.dataId),p=t.readSync(s.dataId),{selectedIndices:m,validOutputs:f}=F7(c,p,a,i,l,u);return[t.makeTensorInfo([m.length],"int32",new Int32Array(m)),t.makeTensorInfo([],"int32",new Int32Array([f]))]}var A$={kernelName:wi,backendName:"webgl",kernelFunc:O7};var P7=Ar.nonMaxSuppressionV5Impl;function M7(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:n}=r,{boxes:o,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=n,c=t.readSync(o.dataId),p=t.readSync(s.dataId),m=a,f=i,d=l,h=u,{selectedIndices:g,selectedScores:x}=P7(c,p,m,f,d,h);return[t.makeTensorInfo([g.length],"int32",new Int32Array(g)),t.makeTensorInfo([x.length],"float32",new Float32Array(x))]}var E$={kernelName:ki,backendName:"webgl",kernelFunc:M7};var Wv=class{constructor(e,t,n,o){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
+`,Rv=nt({opSnippet:Q8,packedOpSnippet:eY,checkOutOfBounds:!0}),JD={kernelName:rn,backendName:"webgl",kernelFunc:Rv};var QD="return a - b;",Fv=nt({opSnippet:QD,packedOpSnippet:QD,supportsComplex:!0,cpuKernelImpl:kE}),e$={kernelName:Fn,backendName:"webgl",kernelFunc:Fv};function Ov(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{dim:s}=o,a=y.parseAxisParam([s],n.shape),i=Sv({inputs:{x:n},backend:t,attrs:{reductionIndices:a,keepDims:!1}}),l=N.expandShapeToKeepDim(i.shape,a),u=pe({inputs:{x:i},backend:t,attrs:{shape:l}}),c=Fv({inputs:{a:n,b:u},backend:t}),p=xv({inputs:{x:c},backend:t}),m=Cf({inputs:{x:p},backend:t,attrs:{axis:a,keepDims:!1}}),f=pe({inputs:{x:m},backend:t,attrs:{shape:l}}),d=Rv({inputs:{a:p,b:f},backend:t});return t.disposeIntermediateTensorInfo(i),t.disposeIntermediateTensorInfo(u),t.disposeIntermediateTensorInfo(c),t.disposeIntermediateTensorInfo(p),t.disposeIntermediateTensorInfo(m),t.disposeIntermediateTensorInfo(f),d}var t$={kernelName:$n,backendName:"webgl",kernelFunc:Ov};function tY(r){let{inputs:e,backend:t,attrs:o}=r,{logits:n}=e,{numSamples:s,seed:a,normalized:i}=o,l=i?n:Ov({inputs:{logits:n},backend:t,attrs:{dim:n.shape.length-1}}),u=l.shape[0],c=l.shape[1],p=new $v(u,c,s),m=p.getCustomSetupFunc(a),f=t.runWebGLProgram(p,[l],"int32",m);return i||t.disposeIntermediateTensorInfo(l),f}var r$={kernelName:su,backendName:"webgl",kernelFunc:tY};var o$="return -x;";function rY(r){let{inputs:e,backend:t}=r,{x:o}=e;if(t.shouldExecuteOnCPU([o])){let s=t.texData.get(o.dataId),[a,i]=hE(s.values,o.shape,o.dtype);return t.makeTensorInfo(i,o.dtype,a)}let n;return W().getBool("WEBGL_PACK_UNARY_OPERATIONS")?n=new Os(o.shape,o$):n=new ao(o.shape,o$),t.runWebGLProgram(n,[o],o.dtype)}var n$={kernelName:ps,backendName:"webgl",kernelFunc:rY};var oY=Ar.nonMaxSuppressionV3Impl;function nY(r){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l}=o,u=t.readSync(n.dataId),c=t.readSync(s.dataId),{selectedIndices:p}=oY(u,c,a,i,l);return t.makeTensorInfo([p.length],"int32",new Int32Array(p))}var s$={kernelName:bi,backendName:"webgl",kernelFunc:nY};var sY=Ar.nonMaxSuppressionV4Impl;function iY(r){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=o,c=t.readSync(n.dataId),p=t.readSync(s.dataId),{selectedIndices:m,validOutputs:f}=sY(c,p,a,i,l,u);return[t.makeTensorInfo([m.length],"int32",new Int32Array(m)),t.makeTensorInfo([],"int32",new Int32Array([f]))]}var i$={kernelName:wi,backendName:"webgl",kernelFunc:iY};var aY=Ar.nonMaxSuppressionV5Impl;function lY(r){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:e,backend:t,attrs:o}=r,{boxes:n,scores:s}=e,{maxOutputSize:a,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=o,c=t.readSync(n.dataId),p=t.readSync(s.dataId),m=a,f=i,d=l,h=u,{selectedIndices:g,selectedScores:x}=aY(c,p,m,f,d,h);return[t.makeTensorInfo([g.length],"int32",new Int32Array(g)),t.makeTensorInfo([x.length],"float32",new Float32Array(x))]}var a$={kernelName:ki,backendName:"webgl",kernelFunc:lY};var Pv=class{constructor(e,t,o,n){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int index = round(getIndices(coords.x));
-        setOutput(mix(float(${o}), float(${n}),
+        setOutput(mix(float(${n}), float(${o}),
                       float(index == coords.y)));
       }
-    `}};var L7=r=>{let{inputs:e,backend:t,attrs:n}=r,{indices:o}=e,{depth:s,onValue:a,offValue:i}=n,l=y.sizeFromShape(o.shape),u=new Wv(l,s,a,i),c=pe({inputs:{x:o},backend:t,attrs:{shape:[l]}}),p=t.runWebGLProgram(u,[c],o.dtype);t.disposeIntermediateTensorInfo(c);let m=[...o.shape,s],f=pe({inputs:{x:p},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(p),f},D$={kernelName:yo,backendName:"webgl",kernelFunc:L7};function Ef(r){let{inputs:e,backend:t}=r,{x:n}=e;if(n.dtype==="complex64"){let o=La({inputs:{input:n},backend:t}),s=Ef({inputs:{x:o},backend:t}),a=tc({inputs:{input:n},backend:t}),i=Ef({inputs:{x:a},backend:t}),l=un({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(o),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),l}else return Af({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:t})}var $$={kernelName:bs,backendName:"webgl",kernelFunc:Ef};function R$(r){let{inputs:e,backend:t}=r,{x:n}=e;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let o=La({inputs:{input:n},backend:t}),s=R$({inputs:{x:o},backend:t}),a=tc({inputs:{input:n},backend:t}),i=Ef({inputs:{x:a},backend:t}),l=un({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(o),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),l}else return Af({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:t})}var F$={kernelName:ms,backendName:"webgl",kernelFunc:R$};function z7(r){let{inputs:e,backend:t,attrs:n}=r,{axis:o}=n;if(e.length===1)return Qg({inputs:{input:e[0]},backend:t,attrs:{dim:o}});let s=e[0].shape,a=e[0].dtype;e.forEach(c=>{y.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),y.assert(a===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=e.map(c=>{let p=Qg({inputs:{input:c},backend:t,attrs:{dim:o}});return i.push(p),p}),u=pv({inputs:l,backend:t,attrs:{axis:o}});return i.forEach(c=>t.disposeIntermediateTensorInfo(c)),u}var O$={kernelName:fs,backendName:"webgl",kernelFunc:z7};var jv=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let o=e.length,s=Le(o),a=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),l=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,o);if(o===1){this.userCode=`
+    `}};var uY=r=>{let{inputs:e,backend:t,attrs:o}=r,{indices:n}=e,{depth:s,onValue:a,offValue:i}=o,l=y.sizeFromShape(n.shape),u=new Pv(l,s,a,i),c=pe({inputs:{x:n},backend:t,attrs:{shape:[l]}}),p=t.runWebGLProgram(u,[c],n.dtype);t.disposeIntermediateTensorInfo(c);let m=[...n.shape,s],f=pe({inputs:{x:p},backend:t,attrs:{shape:m}});return t.disposeIntermediateTensorInfo(p),f},l$={kernelName:yn,backendName:"webgl",kernelFunc:uY};function Af(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="complex64"){let n=La({inputs:{input:o},backend:t}),s=Af({inputs:{x:n},backend:t}),a=ec({inputs:{input:o},backend:t}),i=Af({inputs:{x:a},backend:t}),l=lo({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(n),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),l}else return Tf({attrs:{shape:o.shape,dtype:o.dtype,value:o.dtype==="string"?"":0},backend:t})}var u$={kernelName:bs,backendName:"webgl",kernelFunc:Af};function c$(r){let{inputs:e,backend:t}=r,{x:o}=e;if(o.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(o.dtype==="complex64"){let n=La({inputs:{input:o},backend:t}),s=c$({inputs:{x:n},backend:t}),a=ec({inputs:{input:o},backend:t}),i=Af({inputs:{x:a},backend:t}),l=lo({inputs:{real:s,imag:i},backend:t});return t.disposeIntermediateTensorInfo(n),t.disposeIntermediateTensorInfo(s),t.disposeIntermediateTensorInfo(a),t.disposeIntermediateTensorInfo(i),l}else return Tf({attrs:{shape:o.shape,dtype:o.dtype,value:1},backend:t})}var p$={kernelName:ms,backendName:"webgl",kernelFunc:c$};function cY(r){let{inputs:e,backend:t,attrs:o}=r,{axis:n}=o;if(e.length===1)return Yg({inputs:{input:e[0]},backend:t,attrs:{dim:n}});let s=e[0].shape,a=e[0].dtype;e.forEach(c=>{y.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),y.assert(a===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=e.map(c=>{let p=Yg({inputs:{input:c},backend:t,attrs:{dim:n}});return i.push(p),p}),u=nv({inputs:l,backend:t,attrs:{axis:n}});return i.forEach(c=>t.disposeIntermediateTensorInfo(c)),u}var m$={kernelName:fs,backendName:"webgl",kernelFunc:cY};var Mv=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let n=e.length,s=Le(n),a=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),l=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);if(n===1){this.userCode=`
         int start = ${a};
         int end = ${i};
         uniform float value;
@@ -3421,13 +3421,13 @@ return a / b;`,A7=`
           setOutput(getX(${l}));
         }
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};var Uv=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,g)=>h[0]+e[g]+h[1]);let o=e.length,s=Le(o),a=t.map(h=>h[0]).join(","),i=t.map((h,g)=>h[0]+e[g]).join(","),l=jt("rc",o),u=jt("source",o),c=`${l[o-1]} < ${this.outputShape[o-1]}`,p=o===1?"source":`vec2(${u.slice(-2).join()})`,m=[`${s} rc = outputLoc;`,`${l[o-1]} += 1;
+    `}getCustomSetupFunc(e){return(t,o)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(o,"value")),t.gl.uniform1f(this.valueLoc,e)}}};var Lv=class{constructor(e,t,o){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,g)=>h[0]+e[g]+h[1]);let n=e.length,s=Le(n),a=t.map(h=>h[0]).join(","),i=t.map((h,g)=>h[0]+e[g]).join(","),l=Wt("rc",n),u=Wt("source",n),c=`${l[n-1]} < ${this.outputShape[n-1]}`,p=n===1?"source":`vec2(${u.slice(-2).join()})`,m=[`${s} rc = outputLoc;`,`${l[n-1]} += 1;
        if(${c}) {
-      `,o===1?"":`}
+      `,n===1?"":`}
        rc = outputLoc;
-       ${l[o-2]} += 1;
-       if(${l[o-2]} < ${this.outputShape[o-2]}) {`,o===1?"":`  ${l[o-1]} += 1;
-         if(${c}) {`],f=o===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",d="";for(let h=0,g=o===1?2:4;h<g;h++)d+=`
+       ${l[n-2]} += 1;
+       if(${l[n-2]} < ${this.outputShape[n-2]}) {`,n===1?"":`  ${l[n-1]} += 1;
+         if(${c}) {`],f=n===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",d="";for(let h=0,g=n===1?2:4;h<g;h++)d+=`
         ${m[h]}
         if (${f}) {
           result[${h}] = float(value);
@@ -3435,7 +3435,7 @@ return a / b;`,A7=`
           ${s} source = rc - start;
           result[${h}] = getChannel(getX(${u.join()}), ${p});
         }
-      `;d+=o===1?"} ":"}}",this.userCode=`
+      `;d+=n===1?"} ":"}}",this.userCode=`
       const ${s} start = ${s}(${a});
       const ${s} end = ${s}(${i});
       uniform float value;
@@ -3446,7 +3446,7 @@ return a / b;`,A7=`
         ${d}
         setOutput(result);
       }
-    `}getCustomSetupFunc(e){return(t,n)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(n,"value")),t.gl.uniform1f(this.valueLoc,e)}}};var Hv=r=>{let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{paddings:s,constantValue:a}=n,i=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Uv(o.shape,s,a):new jv(o.shape,s,a),l=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[o],o.dtype,l)},P$={kernelName:bo,backendName:"webgl",kernelFunc:Hv};var B7=`
+    `}getCustomSetupFunc(e){return(t,o)=>{this.valueLoc==null&&(this.valueLoc=t.getUniformLocationNoThrow(o,"value")),t.gl.uniform1f(this.valueLoc,e)}}};var zv=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{paddings:s,constantValue:a}=o,i=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Lv(n.shape,s,a):new Mv(n.shape,s,a),l=i.getCustomSetupFunc(a);return t.runWebGLProgram(i,[n],n.dtype,l)},f$={kernelName:bn,backendName:"webgl",kernelFunc:zv};var pY=`
   if(a < 0.0 && floor(b) < b){
     return NAN;
   }
@@ -3455,7 +3455,7 @@ return a / b;`,A7=`
   }
   return (round(mod(b, 2.0)) != 1) ?
       pow(abs(a), b) : sign(a) * pow(abs(a), b);
-`,V7=`
+`,mY=`
   // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
   vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
   vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
@@ -3471,9 +3471,9 @@ return a / b;`,A7=`
   vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
   `+hl+`
   return result;
-`,G7=ot({opSnippet:B7,packedOpSnippet:V7}),M$={kernelName:wo,backendName:"webgl",kernelFunc:G7};function W7(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{axis:s,keepDims:a}=n,i=o.shape.length,l=[],u=y.parseAxisParam(s,o.shape),c=u,p=S.getAxesPermutation(c,i),m=o;p!=null&&(m=Lt({inputs:{x:o},backend:t,attrs:{perm:p}}),c=S.getInnerMostAxes(c.length,i),l.push(m)),S.assertAxesAreInnerMostDims("prod",c,i);let f;if(t.shouldExecuteOnCPU([m])){let d=t.texData.get(m.dataId).values,{outVals:h,outShape:g,outDtype:x}=zE(m.shape,m.dtype,d,c);f=t.makeTensorInfo(g,x,h)}else{let[d,h]=S.computeOutAndReduceShapes(m.shape,c),g=y.sizeFromShape(h),x=pe({inputs:{x:m},backend:t,attrs:{shape:[-1,g]}}),w=fu(o.dtype),b=Nn(x,w,"prod",t);f=pe({inputs:{x:b},backend:t,attrs:{shape:d}}),l.push(x),l.push(b)}if(a){l.push(f);let d=S.expandShapeToKeepDim(f.shape,u);f=pe({inputs:{x:f},backend:t,attrs:{shape:d}})}return l.forEach(d=>t.disposeIntermediateTensorInfo(d)),f}var L$={kernelName:_i,backendName:"webgl",kernelFunc:W7};var qv=r=>{let{backend:e,attrs:t}=r,{start:n,stop:o,step:s,dtype:a}=t,i=BE(n,o,s,a);return e.makeTensorInfo([i.length],a,i)},z$={kernelName:ca,backendName:"webgl",kernelFunc:qv};var j7="return 1.0 / x;",U7=ke({opSnippet:j7}),B$={kernelName:vi,backendName:"webgl",kernelFunc:U7};var H7=gr+`
+`,fY=nt({opSnippet:pY,packedOpSnippet:mY}),d$={kernelName:wn,backendName:"webgl",kernelFunc:fY};function dY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{axis:s,keepDims:a}=o,i=n.shape.length,l=[],u=y.parseAxisParam(s,n.shape),c=u,p=N.getAxesPermutation(c,i),m=n;p!=null&&(m=Mt({inputs:{x:n},backend:t,attrs:{perm:p}}),c=N.getInnerMostAxes(c.length,i),l.push(m)),N.assertAxesAreInnerMostDims("prod",c,i);let f;if(t.shouldExecuteOnCPU([m])){let d=t.texData.get(m.dataId).values,{outVals:h,outShape:g,outDtype:x}=gE(m.shape,m.dtype,d,c);f=t.makeTensorInfo(g,x,h)}else{let[d,h]=N.computeOutAndReduceShapes(m.shape,c),g=y.sizeFromShape(h),x=pe({inputs:{x:m},backend:t,attrs:{shape:[-1,g]}}),b=fu(n.dtype),w=No(x,b,"prod",t);f=pe({inputs:{x:w},backend:t,attrs:{shape:d}}),l.push(x),l.push(w)}if(a){l.push(f);let d=N.expandShapeToKeepDim(f.shape,u);f=pe({inputs:{x:f},backend:t,attrs:{shape:d}})}return l.forEach(d=>t.disposeIntermediateTensorInfo(d)),f}var h$={kernelName:_i,backendName:"webgl",kernelFunc:dY};var Bv=r=>{let{backend:e,attrs:t}=r,{start:o,stop:n,step:s,dtype:a}=t,i=xE(o,n,s,a);return e.makeTensorInfo([i.length],a,i)},g$={kernelName:ca,backendName:"webgl",kernelFunc:Bv};var hY="return 1.0 / x;",gY=ke({opSnippet:hY}),x$={kernelName:vi,backendName:"webgl",kernelFunc:gY};var xY=gr+`
   return (x < 0.0) ? 0.0 : x;
-`,q7=`
+`,yY=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3483,9 +3483,9 @@ return a / b;`,A7=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,K7=ke({opSnippet:H7,packedOpSnippet:q7}),V$={kernelName:_o,backendName:"webgl",kernelFunc:K7};var X7=gr+`
+`,bY=ke({opSnippet:xY,packedOpSnippet:yY}),y$={kernelName:_n,backendName:"webgl",kernelFunc:bY};var wY=gr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,Y7=`
+`,kY=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
   bvec4 isNaN = isnan(x);
 
@@ -3495,7 +3495,7 @@ return a / b;`,A7=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,Z7=ke({opSnippet:X7,packedOpSnippet:Y7}),G$={kernelName:Co,backendName:"webgl",kernelFunc:Z7};var Kv=class{constructor(e,t,n,o,s){this.variableNames=["A"],this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,n,u];let c=[o&&t>1?i-1:i,o&&n>1?l-1:l],p=[o&&t>1?t-1:t,o&&n>1?n-1:n],m;s?m="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":m="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+`,_Y=ke({opSnippet:wY,packedOpSnippet:kY}),b$={kernelName:Cn,backendName:"webgl",kernelFunc:_Y};var Vv=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?l-1:l],p=[n&&t>1?t-1:t,n&&o>1?o-1:o],m;s?m="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":m="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${c[0]/p[0]},
           ${c[1]/p[1]});
@@ -3528,7 +3528,7 @@ return a / b;`,A7=`
 
         setOutput(newValue);
       }
-    `}};var Xv=class{constructor(e,t,n,o,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,n,u];let c=[o&&t>1?i-1:i,o&&n>1?l-1:l],p=[o&&t>1?t-1:t,o&&n>1?n-1:n],m;s?m="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":m="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};var Gv=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?l-1:l],p=[n&&t>1?t-1:t,n&&o>1?o-1:o],m;s?m="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":m="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec3 effectiveInputOverOutputRatioRC = vec3(
           ${c[0]/p[0]},
           ${c[1]/p[1]},
@@ -3557,7 +3557,7 @@ return a / b;`,A7=`
 
         // Should we calculate next column and row elements in 2x2 packed cell.
         bool hasNextCol = d < ${u-1};
-        bool hasNextRow = coords.z < ${n-1};
+        bool hasNextRow = coords.z < ${o-1};
 
         // In parallel, construct four corners for all four components in
         // packed 2x2 cell.
@@ -3605,7 +3605,7 @@ return a / b;`,A7=`
 
         setOutput(newValue);
       }
-    `}};function J7(r){let{inputs:e,backend:t,attrs:n}=r,{images:o}=e,{alignCorners:s,halfPixelCenters:a,size:i}=n,[l,u]=i,c=j().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Xv(o.shape,l,u,s,a):new Kv(o.shape,l,u,s,a);return t.runWebGLProgram(c,[o],"float32")}var W$={kernelName:vo,backendName:"webgl",kernelFunc:J7};var Yv=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,o,s]=t,[,a,i]=e,l=[n&&a>1?o-1:o,n&&i>1?s-1:s],u=[n&&a>1?a-1:a,n&&i>1?i-1:i],c=l[0]/u[0],p=l[1]/u[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
+    `}};function vY(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,halfPixelCenters:a,size:i}=o,[l,u]=i,c=W().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Gv(n.shape,l,u,s,a):new Vv(n.shape,l,u,s,a);return t.runWebGLProgram(c,[n],"float32")}var w$={kernelName:vn,backendName:"webgl",kernelFunc:vY};var Wv=class{constructor(e,t,o){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,s]=t,[,a,i]=e,l=[o&&a>1?n-1:n,o&&i>1?s-1:s],u=[o&&a>1?a-1:a,o&&i>1?i-1:i],c=l[0]/u[0],p=l[1]/u[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3650,7 +3650,7 @@ return a / b;`,A7=`
 
             float dxR = float(dyR) * heightScale;
             int topDxRIndex = int(floor(dxR));
-            int bottomDxRIndex = int(min(ceil(dxR), ${o-1}.0));
+            int bottomDxRIndex = int(min(ceil(dxR), ${n-1}.0));
             float dxRLerp = dxR - float(topDxRIndex);
             float inverseDxRLerp = 1.0 - dxRLerp;
 
@@ -3686,7 +3686,7 @@ return a / b;`,A7=`
 
         setOutput(accumulator);
       }
-    `}};function Q7(r){let{inputs:e,backend:t,attrs:n}=r,{images:o,dy:s}=e,{alignCorners:a}=n,i=new Yv(s.shape,o.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var j$={kernelName:lu,backendName:"webgl",kernelFunc:Q7};var Zv=class{constructor(e,t,n,o,s){this.variableNames=["A"],this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,n,u];let c=[o&&t>1?i-1:i,o&&n>1?l-1:l],p=[o&&t>1?t-1:t,o&&n>1?n-1:n],m=o?"0.5":"0.0",f;s?f="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":f="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};function CY(r){let{inputs:e,backend:t,attrs:o}=r,{images:n,dy:s}=e,{alignCorners:a}=o,i=new Wv(s.shape,n.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var k$={kernelName:lu,backendName:"webgl",kernelFunc:CY};var jv=class{constructor(e,t,o,n,s){this.variableNames=["A"],this.outputShape=[];let[a,i,l,u]=e;this.outputShape=[a,t,o,u];let c=[n&&t>1?i-1:i,n&&o>1?l-1:l],p=[n&&t>1?t-1:t,n&&o>1?o-1:o],m=n?"0.5":"0.0",f;s?f="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":f="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${c[0]/p[0]},
           ${c[1]/p[1]});
@@ -3708,7 +3708,7 @@ return a / b;`,A7=`
 
         setOutput(newValue);
       }
-    `}};function eY(r){let{inputs:e,backend:t,attrs:n}=r,{images:o}=e,{alignCorners:s,halfPixelCenters:a,size:i}=n,[l,u]=i,c=new Zv(o.shape,l,u,s,a);return t.runWebGLProgram(c,[o],o.dtype)}var U$={kernelName:pa,backendName:"webgl",kernelFunc:eY};var Jv=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,o,s]=t,[,a,i]=e,l=[n&&a>1?o-1:o,n&&i>1?s-1:s],u=[n&&a>1?a-1:a,n&&i>1?i-1:i],c=l[0]/u[0],p=l[1]/u[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
+    `}};function IY(r){let{inputs:e,backend:t,attrs:o}=r,{images:n}=e,{alignCorners:s,halfPixelCenters:a,size:i}=o,[l,u]=i,c=new jv(n.shape,l,u,s,a);return t.runWebGLProgram(c,[n],n.dtype)}var _$={kernelName:pa,backendName:"webgl",kernelFunc:IY};var Uv=class{constructor(e,t,o){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,s]=t,[,a,i]=e,l=[o&&a>1?n-1:n,o&&i>1?s-1:s],u=[o&&a>1?a-1:a,o&&i>1?i-1:i],c=l[0]/u[0],p=l[1]/u[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3760,13 +3760,13 @@ return a / b;`,A7=`
                   (float(dyC) / float(${u[1]}));
 
             int sourceNearestRow = int(min(
-                float(int(${o}) - 1),
-                ${n} ? float(round(sourceFracRow)) :
+                float(int(${n}) - 1),
+                ${o} ? float(round(sourceFracRow)) :
                                   float(floor(sourceFracRow))));
 
             int sourceNearestCol = int(min(
                 float(int(${s}) - 1),
-                ${n} ? float(round(sourceFracCol)) :
+                ${o} ? float(round(sourceFracCol)) :
                                   float(floor(sourceFracCol))));
 
             if (r == sourceNearestRow && c == sourceNearestCol) {
@@ -3778,17 +3778,17 @@ return a / b;`,A7=`
 
         setOutput(accumulator);
       }
-    `}};function tY(r){let{inputs:e,backend:t,attrs:n}=r,{images:o,dy:s}=e,{alignCorners:a}=n,i=new Jv(s.shape,o.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var H$={kernelName:au,backendName:"webgl",kernelFunc:tY};var Qv=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
+    `}};function NY(r){let{inputs:e,backend:t,attrs:o}=r,{images:n,dy:s}=e,{alignCorners:a}=o,i=new Uv(s.shape,n.shape,a);return t.runWebGLProgram(i,[s],s.dtype)}var v$={kernelName:au,backendName:"webgl",kernelFunc:NY};var Hv=class{constructor(e,t){this.variableNames=["x"];let o=e.length;if(o>4)throw new Error(`WebGL backend: Reverse of rank-${o} tensor is not yet supported`);if(this.outputShape=e,o===1){this.userCode=`
         void main() {
           int coord = getOutputCoords();
           setOutput(getX(${e[0]} - coord - 1));
         }
-      `;return}let o=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,s=e.map((i,l)=>o(l)).join(","),a=Le(n);this.userCode=`
+      `;return}let n=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,s=e.map((i,l)=>n(l)).join(","),a=Le(o);this.userCode=`
       void main() {
         ${a} coords = getOutputCoords();
         setOutput(getX(${s}));
       }
-    `}};var eC=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-${n} tensor is not yet supported`);this.outputShape=e;let o=jt("rc",n),s=`${o[n-1]} + 1 < ${this.outputShape[n-1]}`,a=`${o[n-2]} + 1 < ${this.outputShape[n-2]}`,i=Le(n);n===1?this.userCode=`
+    `}};var qv=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let o=e.length;if(o>4)throw new Error(`WebGL backend: Reverse of rank-${o} tensor is not yet supported`);this.outputShape=e;let n=Wt("rc",o),s=`${n[o-1]} + 1 < ${this.outputShape[o-1]}`,a=`${n[o-2]} + 1 < ${this.outputShape[o-2]}`,i=Le(o);o===1?this.userCode=`
         void main(){
           int rc = getOutputCoords();
           vec4 result = vec4(0.);
@@ -3804,19 +3804,19 @@ return a / b;`,A7=`
         void main() {
           ${i} rc = getOutputCoords();
           vec4 result = vec4(0.);
-          result.r = ${l(o.slice())};
+          result.r = ${l(n.slice())};
           if(${s}){
-            result.g = ${u(o.slice())};
+            result.g = ${u(n.slice())};
           }
           if(${a}) {
-            result.b = ${c(o.slice())};
+            result.b = ${c(n.slice())};
             if(${s}) {
-              result.a = ${p(o.slice())};
+              result.a = ${p(n.slice())};
             }
           }
           setOutput(result);
         }
-    `;function l(d){return m(d)}function u(d){return d[n-1]="("+d[n-1]+" + 1)",m(d)}function c(d){return d[n-2]="("+d[n-2]+" + 1)",m(d)}function p(d){return d[n-1]="("+d[n-1]+" + 1)",d[n-2]="("+d[n-2]+" + 1)",m(d)}function m(d){let h=e.map((w,b)=>f(b,d)),g=h.join(","),x=h.slice(-2).join(",");return`getChannel(getX(${g}), vec2(${x}))`}function f(d,h){return t.indexOf(d)!==-1&&e[d]!==1?`${e[d]} - ${h[d]} - 1`:`${h[d]}`}}};function rY(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{dims:s}=n,a=o.shape.length,i=y.parseAxisParam(s,o.shape);if(a===0)return Ut({inputs:{x:o},backend:t});let l=j().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new eC(o.shape,i):new Qv(o.shape,i);return t.runWebGLProgram(l,[o],o.dtype)}var q$={kernelName:Io,backendName:"webgl",kernelFunc:rY};var tC=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let n=e[1],o=e[2];this.outputShape=e;let s="";typeof t=="number"?s=`float outputValue = ${t.toFixed(2)};`:s=`
+    `;function l(d){return m(d)}function u(d){return d[o-1]="("+d[o-1]+" + 1)",m(d)}function c(d){return d[o-2]="("+d[o-2]+" + 1)",m(d)}function p(d){return d[o-1]="("+d[o-1]+" + 1)",d[o-2]="("+d[o-2]+" + 1)",m(d)}function m(d){let h=e.map((b,w)=>f(w,d)),g=h.join(","),x=h.slice(-2).join(",");return`getChannel(getX(${g}), vec2(${x}))`}function f(d,h){return t.indexOf(d)!==-1&&e[d]!==1?`${e[d]} - ${h[d]} - 1`:`${h[d]}`}}};function SY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{dims:s}=o,a=n.shape.length,i=y.parseAxisParam(s,n.shape);if(a===0)return jt({inputs:{x:n},backend:t});let l=W().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new qv(n.shape,i):new Hv(n.shape,i);return t.runWebGLProgram(l,[n],n.dtype)}var C$={kernelName:In,backendName:"webgl",kernelFunc:SY};var Kv=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[];let o=e[1],n=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;
@@ -3831,12 +3831,12 @@ return a / b;`,A7=`
           int coordX = int(round(coordXFloat + params[0]));
           int coordY = int(round(coordYFloat + params[1]));
           ${s}
-          if(coordX >= 0 && coordX < ${o} && coordY >= 0 && coordY < ${n}) {
+          if(coordX >= 0 && coordX < ${n} && coordY >= 0 && coordY < ${o}) {
             outputValue = getImage(coords[0], coordY, coordX, coords[3]);
           }
           setOutput(outputValue);
         }
-    `}getCustomSetupFunc(e,t,n,o){return(s,a)=>{this.paramsLoc==null&&(this.paramsLoc=s.getUniformLocationNoThrow(a,"params")),s.gl.uniform4f(this.paramsLoc,e,t,n,o)}}};var K$={kernelName:$i,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{image:n}=r,{radians:o,fillValue:s,center:a}=e,i=t,l=new tC(n.shape,s),[u,c]=S.getImageCenter(a,n.shape[1],n.shape[2]),p=l.getCustomSetupFunc(u,c,Math.sin(o),Math.cos(o));return i.runWebGLProgram(l,[n],n.dtype,p)}};var nY=`
+    `}getCustomSetupFunc(e,t,o,n){return(s,a)=>{this.paramsLoc==null&&(this.paramsLoc=s.getUniformLocationNoThrow(a,"params")),s.gl.uniform4f(this.paramsLoc,e,t,o,n)}}};var I$={kernelName:$i,backendName:"webgl",kernelFunc:({inputs:r,attrs:e,backend:t})=>{let{image:o}=r,{radians:n,fillValue:s,center:a}=e,i=t,l=new Kv(o.shape,s),[u,c]=N.getImageCenter(a,o.shape[1],o.shape[2]),p=l.getCustomSetupFunc(u,c,Math.sin(n),Math.cos(n));return i.runWebGLProgram(l,[o],o.dtype,p)}};var TY=`
   // OpenGL ES does not support round function.
   // The algorithm is based on banker's rounding.
   float base = floor(x);
@@ -3851,7 +3851,7 @@ return a / b;`,A7=`
       return base + 1.0;
     }
   }
-`,oY=ke({opSnippet:nY}),X$={kernelName:No,backendName:"webgl",kernelFunc:oY};var sY="return inversesqrt(x);",iY=ke({opSnippet:sY,cpuKernelImpl:VE}),Y$={kernelName:So,backendName:"webgl",kernelFunc:iY};var Df=class{constructor(e,t,n,o,s,a,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let l=Le(s.length),u=Le(a.length),c="";n===1?c="i":n===2&&(c="i, j");let p=`getIndices(${c})`,m="";o===1?m="i":o===2&&(m="i, coords[1]");let f=`getUpdates(${m})`,d=t>1?"strides[j]":"strides";this.userCode=`
+`,AY=ke({opSnippet:TY}),N$={kernelName:Nn,backendName:"webgl",kernelFunc:AY};var EY="return inversesqrt(x);",DY=ke({opSnippet:EY,cpuKernelImpl:yE}),S$={kernelName:Sn,backendName:"webgl",kernelFunc:DY};var Ef=class{constructor(e,t,o,n,s,a,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let l=Le(s.length),u=Le(a.length),c="";o===1?c="i":o===2&&(c="i, j");let p=`getIndices(${c})`,m="";n===1?m="i":n===2&&(m="i, coords[1]");let f=`getUpdates(${m})`,d=t>1?"strides[j]":"strides";this.userCode=`
         ${l} strides = ${l}(${s});
 
         void main() {
@@ -3871,31 +3871,31 @@ return a / b;`,A7=`
           }
           setOutput(mix(getDefaultValue(), sum, float(found)));
         }
-      `}};function aY(r){let{inputs:e,backend:t,attrs:n}=r,{indices:o,updates:s}=e,{shape:a}=n,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=S.calculateShapes(s,o,a),m=[p/u,u];if(p===0)return t.makeTensorInfo(a,o.dtype);let f=pe({inputs:{x:o},backend:t,attrs:{shape:[l,i]}}),d=pe({inputs:{x:s},backend:t,attrs:{shape:[l,u]}}),h=t.makeTensorInfo([],"float32",new Float32Array([0])),g=new Df(l,i,f.shape.length,d.shape.length,c,m),x=t.runWebGLProgram(g,[d,f,h],d.dtype),w=pe({inputs:{x},backend:t,attrs:{shape:a}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(x),t.disposeIntermediateTensorInfo(h),w}var Z$={kernelName:Ci,backendName:"webgl",kernelFunc:aY};var rC=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let o,s;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)s="resRC",o="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],l=[],u=[];for(let c=0;c<t.length;c++)u.push(`${i[c]}`),c<e&&l.push(`${i[c]}`);o=l.join(),s=u.join()}let a=Le(n);this.userCode=`
+      `}};function $Y(r){let{inputs:e,backend:t,attrs:o}=r,{indices:n,updates:s}=e,{shape:a}=o,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=N.calculateShapes(s,n,a),m=[p/u,u];if(p===0)return t.makeTensorInfo(a,n.dtype);let f=pe({inputs:{x:n},backend:t,attrs:{shape:[l,i]}}),d=pe({inputs:{x:s},backend:t,attrs:{shape:[l,u]}}),h=t.makeTensorInfo([],"float32",new Float32Array([0])),g=new Ef(l,i,f.shape.length,d.shape.length,c,m),x=t.runWebGLProgram(g,[d,f,h],d.dtype),b=pe({inputs:{x},backend:t,attrs:{shape:a}});return t.disposeIntermediateTensorInfo(f),t.disposeIntermediateTensorInfo(d),t.disposeIntermediateTensorInfo(x),t.disposeIntermediateTensorInfo(h),b}var T$={kernelName:Ci,backendName:"webgl",kernelFunc:$Y};var Xv=class{constructor(e,t,o){this.variableNames=["c","a","b"],this.outputShape=t;let n,s;if(o>4)throw Error(`Where for rank ${o} is not yet supported`);if(o===1)s="resRC",n="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],l=[],u=[];for(let c=0;c<t.length;c++)u.push(`${i[c]}`),c<e&&l.push(`${i[c]}`);n=l.join(),s=u.join()}let a=Le(o);this.userCode=`
       void main() {
         ${a} resRC = getOutputCoords();
-        float cVal = getC(${o});
+        float cVal = getC(${n});
         if (cVal >= 1.0) {
           setOutput(getA(${s}));
         } else {
           setOutput(getB(${s}));
         }
       }
-    `}};function lY(r){let{inputs:e,backend:t}=r,{condition:n,t:o,e:s}=e,a=new rC(n.shape.length,o.shape,o.shape.length);return t.runWebGLProgram(a,[n,o,s],dr(o.dtype,s.dtype))}var J$={kernelName:hs,backendName:"webgl",kernelFunc:lY};var uY=`
+    `}};function RY(r){let{inputs:e,backend:t}=r,{condition:o,t:n,e:s}=e,a=new Xv(o.shape.length,n.shape,n.shape.length);return t.runWebGLProgram(a,[o,n,s],dr(n.dtype,s.dtype))}var A$={kernelName:hs,backendName:"webgl",kernelFunc:RY};var FY=`
   // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
   // see: https://arxiv.org/abs/1706.02515
-  float scaleAlpha = ${S.SELU_SCALEALPHA};
-  float scale = ${S.SELU_SCALE};
+  float scaleAlpha = ${N.SELU_SCALEALPHA};
+  float scale = ${N.SELU_SCALE};
   return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
-`,cY=ke({opSnippet:uY}),Q$={kernelName:Ii,backendName:"webgl",kernelFunc:cY};var pY="return 1.0 / (1.0 + exp(-1.0 * x));",mY=ke({opSnippet:pY}),eR={kernelName:Ao,backendName:"webgl",kernelFunc:mY};var fY=`
+`,OY=ke({opSnippet:FY}),E$={kernelName:Ii,backendName:"webgl",kernelFunc:OY};var PY="return 1.0 / (1.0 + exp(-1.0 * x));",MY=ke({opSnippet:PY}),D$={kernelName:An,backendName:"webgl",kernelFunc:MY};var LY=`
   if (isnan(x)) { return 0.0; }
   return sign(x);
-`,dY=ke({opSnippet:fY}),tR={kernelName:Si,backendName:"webgl",kernelFunc:dY};var hY=jg+`
+`,zY=ke({opSnippet:LY}),$$={kernelName:Si,backendName:"webgl",kernelFunc:zY};var BY=Vg+`
   return sin(x);
-`,gY=ke({opSnippet:hY}),rR={kernelName:To,backendName:"webgl",kernelFunc:gY};var xY=`
+`,VY=ke({opSnippet:BY}),R$={kernelName:Tn,backendName:"webgl",kernelFunc:VY};var GY=`
   float e2x = exp(x);
   return (e2x - 1.0 / e2x) / 2.0;
-`,yY=ke({opSnippet:xY}),nR={kernelName:Ni,backendName:"webgl",kernelFunc:yY};var bY=`
+`,WY=ke({opSnippet:GY}),F$={kernelName:Ni,backendName:"webgl",kernelFunc:WY};var jY=`
   float epsilon = 1.1920928955078125e-7;
   float threshold = log(epsilon) + 2.0;
 
@@ -3915,9 +3915,9 @@ return a / b;`,A7=`
     result = log(exp_x + 1.0);
   }
   return result;
-`,wY=ke({opSnippet:bY}),oR={kernelName:Ti,backendName:"webgl",kernelFunc:wY};var kY=r=>{let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{blockShape:s,paddings:a}=n;y.assert(o.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let i=s.reduce((x,w)=>x*w),l=[[0,0]];l.push(...a);for(let x=1+s.length;x<o.shape.length;++x)l.push([0,0]);let u=[],c=Hv({inputs:{x:o},backend:t,attrs:{paddings:l,constantValue:0}}),p=S.getReshaped(c.shape,s,i,!1),m=S.getPermuted(p.length,s.length,!1),f=S.getReshapedPermuted(c.shape,s,i,!1),d=pe({inputs:{x:c},backend:t,attrs:{shape:p}}),h=Lt({inputs:{x:d},backend:t,attrs:{perm:m}}),g=pe({inputs:{x:h},backend:t,attrs:{shape:f}});return u.push(c),u.push(d),u.push(h),u.forEach(x=>t.disposeIntermediateTensorInfo(x)),g},sR={kernelName:ma,backendName:"webgl",kernelFunc:kY};function _Y(r){let{inputs:e,backend:t,attrs:n}=r,{sparseIndices:o,sparseValues:s,defaultValue:a}=e,{outputShape:i}=n,{sliceRank:l,numUpdates:u,strides:c,outputSize:p}=S.calculateShapes(s,o,i),m=!1,f=new Df(u,l,o.shape.length,s.shape.length,c,[p,1],m),d=t.runWebGLProgram(f,[s,o,a],s.dtype),h=pe({inputs:{x:d},backend:t,attrs:{shape:i}});return t.disposeIntermediateTensorInfo(d),h}var iR={kernelName:uu,backendName:"webgl",kernelFunc:_Y};function vY(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{numOrSizeSplits:s,axis:a}=n,i=y.parseAxisParam(a,o.shape)[0],l=S.prepareSplitSize(o,s,i),u=o.shape.length,c=new Array(u).fill(0),p=o.shape.slice();return l.map(m=>{let f=[...p];f[i]=m;let d=Ma({inputs:{x:o},backend:t,attrs:{begin:c,size:f}});return c[i]+=m,d})}var aR={kernelName:xs,backendName:"webgl",kernelFunc:vY};var CY="return sqrt(x);",IY=ke({opSnippet:CY}),lR={kernelName:Eo,backendName:"webgl",kernelFunc:IY};var NY="return x * x;",SY=ke({opSnippet:NY}),uR={kernelName:fa,backendName:"webgl",kernelFunc:SY};var cR="return (a - b) * (a - b);",TY=ot({opSnippet:cR,packedOpSnippet:cR}),pR={kernelName:Ro,backendName:"webgl",kernelFunc:TY};function AY({inputs:r,attrs:e,backend:t}){let{x:n}=r,o=gr+`
+`,UY=ke({opSnippet:jY}),O$={kernelName:Ti,backendName:"webgl",kernelFunc:UY};var HY=r=>{let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{blockShape:s,paddings:a}=o;y.assert(n.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let i=s.reduce((x,b)=>x*b),l=[[0,0]];l.push(...a);for(let x=1+s.length;x<n.shape.length;++x)l.push([0,0]);let u=[],c=zv({inputs:{x:n},backend:t,attrs:{paddings:l,constantValue:0}}),p=N.getReshaped(c.shape,s,i,!1),m=N.getPermuted(p.length,s.length,!1),f=N.getReshapedPermuted(c.shape,s,i,!1),d=pe({inputs:{x:c},backend:t,attrs:{shape:p}}),h=Mt({inputs:{x:d},backend:t,attrs:{perm:m}}),g=pe({inputs:{x:h},backend:t,attrs:{shape:f}});return u.push(c),u.push(d),u.push(h),u.forEach(x=>t.disposeIntermediateTensorInfo(x)),g},P$={kernelName:ma,backendName:"webgl",kernelFunc:HY};function qY(r){let{inputs:e,backend:t,attrs:o}=r,{sparseIndices:n,sparseValues:s,defaultValue:a}=e,{outputShape:i}=o,{sliceRank:l,numUpdates:u,strides:c,outputSize:p}=N.calculateShapes(s,n,i),m=!1,f=new Ef(u,l,n.shape.length,s.shape.length,c,[p,1],m),d=t.runWebGLProgram(f,[s,n,a],s.dtype),h=pe({inputs:{x:d},backend:t,attrs:{shape:i}});return t.disposeIntermediateTensorInfo(d),h}var M$={kernelName:uu,backendName:"webgl",kernelFunc:qY};function KY(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{numOrSizeSplits:s,axis:a}=o,i=y.parseAxisParam(a,n.shape)[0],l=N.prepareSplitSize(n,s,i),u=n.shape.length,c=new Array(u).fill(0),p=n.shape.slice();return l.map(m=>{let f=[...p];f[i]=m;let d=Ma({inputs:{x:n},backend:t,attrs:{begin:c,size:f}});return c[i]+=m,d})}var L$={kernelName:xs,backendName:"webgl",kernelFunc:KY};var XY="return sqrt(x);",YY=ke({opSnippet:XY}),z$={kernelName:En,backendName:"webgl",kernelFunc:YY};var ZY="return x * x;",JY=ke({opSnippet:ZY}),B$={kernelName:fa,backendName:"webgl",kernelFunc:JY};var V$="return (a - b) * (a - b);",QY=nt({opSnippet:V$,packedOpSnippet:V$}),G$={kernelName:Rn,backendName:"webgl",kernelFunc:QY};function e7({inputs:r,attrs:e,backend:t}){let{x:o}=r,n=gr+`
     return x > 0.0 ? 1.0 : float(${e.alpha});
-  `,s=new ln(n.shape,o);return t.runWebGLProgram(s,[n],n.dtype)}var mR={kernelName:On,backendName:"webgl",kernelFunc:AY};var nC=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let o=n.length,s=Le(n.length),a=Le(n.length),i="";if(o===1)i="coords * strides + begin";else{let l=0;i=n.map((u,c)=>(l++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${l-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
+  `,s=new ao(o.shape,n);return t.runWebGLProgram(s,[o],o.dtype)}var W$={kernelName:Oo,backendName:"webgl",kernelFunc:e7};var Yv=class{constructor(e,t,o){this.variableNames=["x"],this.outputShape=o;let n=o.length,s=Le(o.length),a=Le(o.length),i="";if(n===1)i="coords * strides + begin";else{let l=0;i=o.map((u,c)=>(l++,o.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${l-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
       ${s} begin = ${s}(${e});
       ${s} strides = ${s}(${t});
 
@@ -3925,15 +3925,15 @@ return a / b;`,A7=`
         ${a} coords = getOutputCoords();
         setOutput(getX(${i}));
       }
-    `}};function EY(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{begin:s,end:a,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:m}=n,{nonStrided:f,$begin:d,$strides:h,size:g,newShape:x,outShape:w}=sr.sliceInfo(o.shape,s,a,i,l,u,c,p,m),b=pe({inputs:{x:o},backend:t,attrs:{shape:x}}),k;if(f){let A=Ma({inputs:{x:b},backend:t,attrs:{begin:d,size:g}});k=pe({inputs:{x:A},backend:t,attrs:{shape:w}}),t.disposeIntermediateTensorInfo(A)}else if(w.some(A=>A===0))k=t.makeTensorInfo(w,o.dtype,[]);else if(t.shouldExecuteOnCPU([b])){let $=t.texData.get(b.dataId).values,F=ve(b.shape,b.dtype,$),M=WE(w,F,h,d);k=t.makeTensorInfo(w,b.dtype,M.values)}else{let N=new nC(d,h,w);k=t.runWebGLProgram(N,[b],b.dtype)}let _=pe({inputs:{x:k},backend:t,attrs:{shape:w}});return t.disposeIntermediateTensorInfo(b),t.disposeIntermediateTensorInfo(k),_}var fR={kernelName:Ai,backendName:"webgl",kernelFunc:EY};var DY="return tan(x);",$Y=ke({opSnippet:DY}),dR={kernelName:Ei,backendName:"webgl",kernelFunc:$Y};var RY=`
+    `}};function t7(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{begin:s,end:a,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:m}=o,{nonStrided:f,$begin:d,$strides:h,size:g,newShape:x,outShape:b}=sr.sliceInfo(n.shape,s,a,i,l,u,c,p,m),w=pe({inputs:{x:n},backend:t,attrs:{shape:x}}),k;if(f){let D=Ma({inputs:{x:w},backend:t,attrs:{begin:d,size:g}});k=pe({inputs:{x:D},backend:t,attrs:{shape:b}}),t.disposeIntermediateTensorInfo(D)}else if(b.some(D=>D===0))k=t.makeTensorInfo(b,n.dtype,[]);else if(t.shouldExecuteOnCPU([w])){let R=t.texData.get(w.dataId).values,O=ve(w.shape,w.dtype,R),M=wE(b,O,h,d);k=t.makeTensorInfo(b,w.dtype,M.values)}else{let T=new Yv(d,h,b);k=t.runWebGLProgram(T,[w],w.dtype)}let _=pe({inputs:{x:k},backend:t,attrs:{shape:b}});return t.disposeIntermediateTensorInfo(w),t.disposeIntermediateTensorInfo(k),_}var j$={kernelName:Ai,backendName:"webgl",kernelFunc:t7};var r7="return tan(x);",o7=ke({opSnippet:r7}),U$={kernelName:Ei,backendName:"webgl",kernelFunc:o7};var n7=`
   float e2x = exp(-2.0 * abs(x));
   return sign(x) * (1.0 - e2x) / (1.0 + e2x);
-`,FY=ke({opSnippet:RY}),hR={kernelName:Oo,backendName:"webgl",kernelFunc:FY};var oC=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 o=Le(this.rank),s=OY(e);this.userCode=`
+`,s7=ke({opSnippet:n7}),H$={kernelName:On,backendName:"webgl",kernelFunc:s7};var Zv=class{constructor(e,t){this.variableNames=["A"];let o=new Array(e.length);for(let a=0;a<o.length;a++)o[a]=e[a]*t[a];this.outputShape=o,this.rank=o.length;let n=Le(this.rank),s=i7(e);this.userCode=`
       void main() {
-        ${o} resRC = getOutputCoords();
+        ${n} resRC = getOutputCoords();
         setOutput(getA(${s}));
       }
-    `}};function OY(r){let e=r.length;if(e>5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`imod(resRC, ${r[0]})`;let t=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[];for(let o=0;o<r.length;o++)n.push(`imod(${t[o]}, ${r[o]})`);return n.join()}function sC(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{reps:s}=n;if(o.dtype==="string"){let u=t.readSync(o.dataId).map(m=>y.decodeString(m)),c=ve(o.shape,o.dtype,u),p=UE(c,s);return t.makeTensorInfo(p.shape,p.dtype,p.values)}let a=new oC(o.shape,s);return t.runWebGLProgram(a,[o],o.dtype)}var gR={kernelName:kn,backendName:"webgl",kernelFunc:sC};function PY(r){let{inputs:e,backend:t,attrs:n}=r,{x:o}=e,{k:s,sorted:a}=n,i=t.readSync(o.dataId),[l,u]=HE(i,o.shape,o.dtype,s,a);return[t.makeTensorInfo(l.shape,l.dtype,l.values),t.makeTensorInfo(u.shape,u.dtype,u.values)]}var xR={kernelName:Di,backendName:"webgl",kernelFunc:PY};var iC=class{constructor(e,t,n,o,s,a){this.variableNames=["Image","Transforms"],this.outputShape=a;let i=n==="nearest"?1:2,l;switch(o){case"constant":l=1;break;case"reflect":l=2;break;case"wrap":l=3;break;case"nearest":l=4;break;default:l=1;break}this.userCode=`
+    `}};function i7(r){let e=r.length;if(e>5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`imod(resRC, ${r[0]})`;let t=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],o=[];for(let n=0;n<r.length;n++)o.push(`imod(${t[n]}, ${r[n]})`);return o.join()}function Jv(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{reps:s}=o;if(n.dtype==="string"){let u=t.readSync(n.dataId).map(m=>y.decodeString(m)),c=ve(n.shape,n.dtype,u),p=_E(c,s);return t.makeTensorInfo(p.shape,p.dtype,p.values)}let a=new Zv(n.shape,s);return t.runWebGLProgram(a,[n],n.dtype)}var q$={kernelName:ko,backendName:"webgl",kernelFunc:Jv};function a7(r){let{inputs:e,backend:t,attrs:o}=r,{x:n}=e,{k:s,sorted:a}=o,i=t.readSync(n.dataId),[l,u]=vE(i,n.shape,n.dtype,s,a);return[t.makeTensorInfo(l.shape,l.dtype,l.values),t.makeTensorInfo(u.shape,u.dtype,u.values)]}var K$={kernelName:Di,backendName:"webgl",kernelFunc:a7};var Qv=class{constructor(e,t,o,n,s,a){this.variableNames=["Image","Transforms"],this.outputShape=a;let i=o==="nearest"?1:2,l;switch(n){case"constant":l=1;break;case"reflect":l=2;break;case"wrap":l=3;break;case"nearest":l=4;break;default:l=1;break}this.userCode=`
             float mapCoord(float outCoord, float len) {
               float inCoord = outCoord;
               if(${l} == 2) {
@@ -4045,13 +4045,13 @@ return a / b;`,A7=`
               }
               setOutput(outputValue);
             }
-        `}};function MY(r){let{inputs:e,backend:t,attrs:n}=r,{image:o,transforms:s}=e,{interpolation:a,fillMode:i,fillValue:l,outputShape:u}=n,[c,p,m,f]=o.shape,[d,h]=u!=null?u:[p,m],g=[c,d,h,f],x=new iC(p,m,a,i,l,g);return t.runWebGLProgram(x,[o,s],"float32")}var yR={kernelName:cu,backendName:"webgl",kernelFunc:MY};function LY(r){let{inputs:e,attrs:t,backend:n}=r,{axis:o}=t,{x:s}=e;Rs(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let a=n.readSync(s.dataId),{outputValues:i,outputShape:l,indices:u}=qE(a,o,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,i),n.makeTensorInfo([u.length],"int32",u)]}var bR={kernelName:pu,backendName:"webgl",kernelFunc:LY};function zY(r){let{inputs:e,backend:t,attrs:n}=r,{value:o}=e,{axis:s}=n;s<0&&(s+=o.shape.length);let a=o,i=a.shape.length,l=o.shape[s],u=new Array(i-1),c=0;for(let h=0;h<i;h++)h!==s&&(u[c++]=a.shape[h]);let p=[],m=new Array(i).fill(0),f=a.shape.slice();f[s]=1;let d=new Array(l);for(let h=0;h<d.length;h++){m[s]=h;let g=Ma({inputs:{x:a},backend:t,attrs:{begin:m,size:f}}),x=pe({inputs:{x:g},backend:t,attrs:{shape:u}});d[h]=x,p.push(g)}return p.forEach(h=>t.disposeIntermediateTensorInfo(h)),d}var wR={kernelName:ys,backendName:"webgl",kernelFunc:zY};var aC=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,o=e.batchSize,s=e.inSize,a=e.numSegments,i=a*Math.ceil(s/n);this.outputShape=[o,i];let l="0.0",u="sumValue",c=Math.floor(n/4)*4,p=n%4,m=`
+        `}};function l7(r){let{inputs:e,backend:t,attrs:o}=r,{image:n,transforms:s}=e,{interpolation:a,fillMode:i,fillValue:l,outputShape:u}=o,[c,p,m,f]=n.shape,[d,h]=u!=null?u:[p,m],g=[c,d,h,f],x=new Qv(p,m,a,i,l,g);return t.runWebGLProgram(x,[n,s],"float32")}var X$={kernelName:cu,backendName:"webgl",kernelFunc:l7};function u7(r){let{inputs:e,attrs:t,backend:o}=r,{axis:n}=t,{x:s}=e;Rs(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let a=o.readSync(s.dataId),{outputValues:i,outputShape:l,indices:u}=CE(a,n,s.shape,s.dtype);return[o.makeTensorInfo(l,s.dtype,i),o.makeTensorInfo([u.length],"int32",u)]}var Y$={kernelName:pu,backendName:"webgl",kernelFunc:u7};function c7(r){let{inputs:e,backend:t,attrs:o}=r,{value:n}=e,{axis:s}=o;s<0&&(s+=n.shape.length);let a=n,i=a.shape.length,l=n.shape[s],u=new Array(i-1),c=0;for(let h=0;h<i;h++)h!==s&&(u[c++]=a.shape[h]);let p=[],m=new Array(i).fill(0),f=a.shape.slice();f[s]=1;let d=new Array(l);for(let h=0;h<d.length;h++){m[s]=h;let g=Ma({inputs:{x:a},backend:t,attrs:{begin:m,size:f}}),x=pe({inputs:{x:g},backend:t,attrs:{shape:u}});d[h]=x,p.push(g)}return p.forEach(h=>t.disposeIntermediateTensorInfo(h)),d}var Z$={kernelName:ys,backendName:"webgl",kernelFunc:c7};var eC=class{constructor(e,t){this.variableNames=["x","segmentIds"];let o=e.windowSize,n=e.batchSize,s=e.inSize,a=e.numSegments,i=a*Math.ceil(s/o);this.outputShape=[n,i];let l="0.0",u="sumValue",c=Math.floor(o/4)*4,p=o%4,m=`
         sumValue += dot(values, segFilter);
-    `,f="";s%n>0&&(f=`
+    `,f="";s%o>0&&(f=`
         if (inIdx < 0 || inIdx >= ${s}) {
           return initializationValue;
         }
-      `);let d="";s%n>0&&(d=`
+      `);let d="";s%o>0&&(d=`
         if (inIdx < 0 || inIdx >= ${s}) {
           return -1.0;
         }
@@ -4073,7 +4073,7 @@ return a / b;`,A7=`
         int batch = coords[0];
         int outIdx = coords[1];
         int inOffset = int(floor(float(outIdx) / float(
-          ${a})) * float(${n}));
+          ${a})) * float(${o}));
         int currentSeg = int(mod(float(outIdx), float(${a})));
 
         float sumValue = 0.0;
@@ -4151,19 +4151,19 @@ return a / b;`,A7=`
         }
         setOutput(${u});
       }
-    `}};function BY(r){let{inputs:e,backend:t,attrs:n}=r,{x:o,segmentIds:s}=e,{numSegments:a}=n,i=o.shape.length,l=[],u=0,c=S.getAxesPermutation([u],i),p=o;c!=null&&(p=Lt({inputs:{x:o},backend:t,attrs:{perm:c}}),l.push(p),u=S.getInnerMostAxes(1,i)[0]);let m=S.segment_util.computeOutShape(p.shape,u,a),f=y.sizeFromShape([p.shape[u]]),d=pe({inputs:{x:p},backend:t,attrs:{shape:[-1,f]}});l.push(d);let h=fu(o.dtype),g=(k,_,A,N,$)=>{let F=k.shape[0],M=k.shape[1],V=S.segment_util.segOpComputeOptimalWindowSize(M,$),W={windowSize:V,inSize:M,batchSize:F,numSegments:$},U=new aC(W,_),H=t.compileAndRun(U,[k,A],N);if(l.push(H),H.shape[1]===$)return H;let q=qv({backend:t,attrs:{start:0,stop:$,step:1,dtype:"float32"}}),X=sC({inputs:{x:q},backend:t,attrs:{reps:[M/V]}});return l.push(q),l.push(X),g(H,_,X,N,$)},x=g(d,"unsortedSegmentSum",s,h,a),w=pe({inputs:{x},backend:t,attrs:{shape:m}}),b=w;if(c!=null){l.push(w);let k=S.getUndoAxesPermutation(c);b=Lt({inputs:{x:b},backend:t,attrs:{perm:k}})}return 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Uint8Array(new Int32Array(s.shape).buffer);return _R(m,A,o.shape.length,f,N,s.shape.length,l,u,g,d,h,p||0,_),k}var vR={kernelName:ws,backendName:"wasm",setupFunc:GY,kernelFunc:WY};function St(r){let e;function t(o){e=o.wasm.cwrap(r,null,["number","number"])}function n(o){let{backend:s,inputs:{x:a}}=o,i=s.dataIdMap.get(a.dataId).id,l=s.makeOutput(a.shape,a.dtype),u=s.dataIdMap.get(l.dataId).id;return y.sizeFromShape(l.shape)===0||e(i,u),l}return{kernelName:r,backendName:"wasm",setupFunc:t,kernelFunc:n}}var CR=St(as);function yt(r,e,t){let n;function o(a){n=a.wasm.cwrap(r,null,["number","array","number","number","array","number","number","number"])}function s(a){let{backend:i,inputs:l}=a,{a:u,b:c}=l,p=i.dataIdMap.get(u.dataId).id,m=i.dataIdMap.get(c.dataId).id,f=t!=null?t:u.dtype,d=S.assertAndGetBroadcastShape(u.shape,c.shape),h=i.makeOutput(d,f);if(y.sizeFromShape(d)===0)return h;let g=new Uint8Array(new Int32Array(u.shape).buffer),x=new Uint8Array(new 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nc(r){let{inputs:{x:e},backend:t}=r,n=t.makeOutput(e.shape,e.dtype),o=t.typedArrayFromHeap(e);return t.typedArrayFromHeap(n).set(o),n}var TR={kernelName:Fn,backendName:"wasm",kernelFunc:nc};var AR;function qY(r){AR=r.wasm.cwrap(Po,null,["number","array","number","number","number","array","number"])}function vp(r){let{inputs:e,backend:t,attrs:n}=r,[o,s]=XY(e.x.shape,n.perm),a=!0;for(let d=0;d<s.length;d++)s[d]!==d&&(a=!1);let i=KY(e.x.shape,n.perm),l={dataId:e.x.dataId,shape:o,dtype:e.x.dtype};if(a){let d=nc({inputs:e,backend:t});return d.shape=i,d}let u=t.makeOutput(i,l.dtype),c=t.dataIdMap.get(l.dataId).id,p=t.dataIdMap.get(u.dataId).id,m=new Uint8Array(new Int32Array(s).buffer),f=new Uint8Array(new Int32Array(l.shape).buffer);return AR(c,f,l.shape.length,zt[l.dtype],p,m,s.length),u}function KY(r,e){let t=new Array(r.length);for(let n=0;n<t.length;n++)t[n]=r[e[n]];return t}function XY(r,e){let t=[],n=[];for(let o=0;o<r.length;++o)r[o]!==1&&t.push(r[o]),r[e[o]]!==1&&n.push(e[o]);for(let o=0;o<n.length;++o){let s=-1;for(let a=0;a<n.length;++a)n[a]>=o&&(s===-1||n[s]>n[a])&&(s=a);n[s]=o}return[t,n]}var ER={kernelName:Po,backendName:"wasm",kernelFunc:vp,setupFunc:qY};function Yo(r,e,t){let n=r.shape,o=r.shape.length,s=y.parseAxisParam(e,n),a=s,i=S.getAxesPermutation(a,o),l=null,u=!1;if(i!=null){let c=new Array(o);for(let f=0;f<c.length;f++)c[f]=n[i[f]];a=S.getInnerMostAxes(a.length,o),l=vp({inputs:{x:r},attrs:{perm:i},backend:t});let p=t.dataIdMap.get(r.dataId).id;t.dataIdMap.get(l.dataId).id!==p&&(u=!0)}return{transposed:l,originalAxes:s,axes:a,inputWasTransposed:u}}var DR;function YY(r){DR=r.wasm.cwrap(qn,null,["number","number","number","number","number"])}function ZY(r){let{backend:e,inputs:t,attrs:n}=r,{axis:o}=n,{x:s}=t,a=e.dataIdMap.get(s.dataId).id,i=a,l=s,{transposed:u,axes:c,inputWasTransposed:p}=Yo(s,o,e);if(p){let x=e.dataIdMap.get(u.dataId).id;x!==a&&(l=u,i=x)}let m=l.shape.slice(0,-1),f=e.makeOutput(m,"int32"),d=e.dataIdMap.get(f.dataId).id,h=y.sizeFromShape(f.shape),g=l.shape[c[0]];return DR(i,zt[l.dtype],h,g,d),p&&e.disposeData(u.dataId),f}var $R={kernelName:qn,backendName:"wasm",kernelFunc:ZY,setupFunc:YY};var RR;function JY(r){RR=r.wasm.cwrap(Kn,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function QY(r){let{inputs:e,attrs:t,backend:n}=r,o=e.x,s=n.dataIdMap.get(o.dataId).id,{filterSize:a,strides:i,pad:l,dimRoundingMode:u}=t,c=S.computePool2DInfo(o.shape,a,i,1,l,u),p=c.filterHeight,m=c.filterWidth,f=c.padInfo.top,d=c.padInfo.right,h=c.padInfo.bottom,g=c.padInfo.left,x=c.strideHeight,w=c.strideWidth,b=c.inChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. 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They will not be included in the serialized model (and thus will be missing at deserialization time).`),d={}}if(m.inboundLayers.length>0){let h=[];for(let g=0;g<m.inboundLayers.length;g++){let x=m.inboundLayers[g],w=m.nodeIndices[g],b=m.tensorIndices[g],k=Wn.nodeKey(x,w),_=t[k];_==null&&(_=0),h.push([x.name,_,b,d])}u.push(h)}}}let c={};c.name=a.name,c.className=i,c.config=l,c.inboundNodes=u,n.push(c)}e.layers=n;let o=[];for(let a=0;a<this.inputLayers.length;a++){let i=this.inputLayers[a],l=this.inputLayersNodeIndices[a],u=Wn.nodeKey(i,l);if(!this.containerNodes.has(u))continue;let c=t[u];c==null&&(c=0);let p=this.inputLayersTensorIndices[a];o.push([i.name,c,p])}e.inputLayers=o;let s=[];for(let a=0;a<this.outputLayers.length;a++){let i=this.outputLayers[a],l=this.outputLayersNodeIndices[a],u=Wn.nodeKey(i,l);if(!this.containerNodes.has(u))continue;let c=t[u];c==null&&(c=0);let p=this.outputLayersTensorIndices[a];s.push([i.name,c,p])}return e.outputLayers=s,e}static fromConfig(e,t,n={},o=!1){let s={},a={};function i(g,x){g.name in a?a[g.name].push(x):a[g.name]=[x]}function l(g,x){let w=[],b;for(let k of x){let _=k[0],A=k[1],N=k[2];if(b=k[3]==null?{}:k[3],!(_ in s)){i(g,x);return}let $=s[_];if($.inboundNodes.length<=A){i(g,x);return}let F=$.inboundNodes[A];w.push(F.outputTensors[N])}w.length>0&&g.apply(xr(w),b)}function u(g){let x=g.name,w=Qr(g,t.customObjects!=null?t.customObjects:{});w.setFastWeightInitDuringBuild(o),s[x]=w,g.inboundNodes.forEach(k=>{if(!(k instanceof Array))throw new z(`Corrupted configuration, expected array for nodeData: ${k}`);i(w,k)})}let c=t.name,p=t.layers;for(let g of p)u(g);for(;!qM(a);)for(let g of p){let x=s[g.name];if(x.name in a){let w=a[x.name];delete a[x.name];for(let b of w)l(x,b)}}let m=[],f=[],d=t.inputLayers;for(let g of d){let x=g[0],w=g[1],b=g[2];Gn(x in s);let _=s[x].inboundNodes[w].outputTensors;m.push(_[b])}let h=t.outputLayers;for(let g of h){let x=g[0],w=g[1],b=g[2];Gn(x in s);let _=s[x].inboundNodes[w].outputTensors;f.push(_[b])}return new e({inputs:m,outputs:f,name:c})}get stateful(){if(this._stateful)throw new z("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");for(let e of this.layers)if(e.stateful)return!0;return!1}resetStates(){G(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function pQ(r,e,t){let n=e.length;if(r==null||Array.isArray(r)&&r.length===0)return e.map(o=>null);if(n===1)return Array.isArray(r)&&r.length===1?r:typeof r=="object"&&e[0]in r?[r[e[0]]]:[r];if(Array.isArray(r)){if(r.length!==n)throw new Error(`Provided ${t} is an array of ${r.length} element(s), but the model has ${n} outputs. Make sure a set of weights is provided for each model output.`);return r}else if(typeof r=="object"&&Object.keys(r).length>0&&typeof r[Object.keys(r)[0]]=="object"){let o=[];return e.forEach(s=>{s in r?o.push(r[s]):o.push(null)}),o}else throw new Error(`The model has multiple (${n}) outputs, so ${t} must be either an array with ${n} elements or an object with ${e} keys. Provided ${t} not understood: ${JSON.stringify(r)}`)}function $x(r,e){return pQ(r,e,"classWeight")}async function Rx(r,e,t,n){if(e!=null||n!=null)throw new Error("Support sampleWeight is not implemented yet");if(t!=null){let o=G(()=>{if(r.shape.length===1)return r.clone();if(r.shape.length===2)if(r.shape[1]>1){let i=1;return r.argMax(i)}else{if(r.shape[1]===1)return r.reshape([r.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${r.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${r.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await o.data());Ae(o);let a=[];return s.forEach(i=>{if(t[i]==null)throw new Error(`classWeight must contain all classes in the training data. The class ${i} exists in the data but not in classWeight`);a.push(t[i])}),Gt(a,"float32")}else return null}function EL(r,e){return P(r,e)}var mQ=32;function $L(r,e){let t,n,o=e;t=o.xs,n=o.ys,y.assert(t!=null&&n!=null,()=>`A Dataset iterator for fitDataset() is expected to generate objects of the form \`{xs: xVal, ys: yVal}\`, where the two values may be \`tf.Tensor\`, an array of Tensors, or a map of string to Tensor.  The provided Dataset instead generates ${e}`);let s=DL("input",r.inputNames,t),a=DL("output",r.outputNames,n),i=s[0].shape[0];y.assert(s.length===r.inputs.length,()=>`LayersModel has ${r.inputs.length} inputs, but the dataset provides ${s.length} inputs.  (Expected input keys: ${JSON.stringify(r.inputNames)})`),y.assert(a.length===r.outputs.length,()=>`LayersModel has ${r.outputs.length} outputs, but the dataset provides ${a.length} outputs.  (Expected output keys: ${JSON.stringify(r.outputNames)})`);for(let l=0;l<s.length;l++)y.assert(s[l].shape[0]===i,()=>`Batch size mismatch: input ${r.inputNames[l]} has ${s[l].shape[0]}; expected  ${i} based on input ${r.inputNames[0]}.`);for(let l=0;l<a.length;l++)y.assert(a[l].shape[0]===i,()=>`Batch size mismatch: output ${r.outputNames[l]} has ${a[l].shape[0]}; expected  ${i} based on input ${r.inputNames[0]}.`);return{xs:s,ys:a}}function DL(r,e,t){if(t instanceof Ve)return[t];if(Array.isArray(t))return y.assert(t.length===e.length,()=>`Received an array of ${t.length} Tensors, but expected ${e.length} to match the ${r} keys ${e}.`),t;{let n=[];for(let o of e){if(t[o]==null)throw new z(`The feature data generated by the dataset lacks the required ${r} key '${o}'.`);n.push(t[o])}return n}}function fQ(r){if(r.length===3)throw new Se("Validation with sample weights is not implemented yet.");return{xs:r[0],ys:r[1]}}async function FL(r,e,t){let n=t.batchesPerEpoch!=null;if(y.assert(r.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),y.assert(t!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),y.assert(t.epochs!=null&&t.epochs>0&&Number.isInteger(t.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${t.epochs}`),y.assert(!n||t.batchesPerEpoch>0&&Number.isInteger(t.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${t.batchesPerEpoch}`),y.assert(t.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. 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t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),o=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),a=[],i=()=>{let p=[];for(let h=0;h<this.inputs.length;++h)p.push({key:this.inputs[h],value:n[h]});let m=new zs(p),f=pc(this.outputs,m,{training:!0}),d;for(let h=0;h<this.lossFunctions.length;++h){let x=this.lossFunctions[h](o[h],f[h]);s[h]!=null&&(x=EL(x,s[h]));let w=ht(x);t.push(w),h===0?d=x:d=ee(d,x)}for(let h=0;h<this.metricsTensors.length;++h){let g;if(this.outputs.length>1&&h<this.outputs.length)g=t[h];else{let x=this.metricsTensors[h][0],w=this.metricsTensors[h][1];g=ht(x(o[w],f[w]))}Dt(g),a.push(g)}return d=ht(d),this.calculateLosses().forEach(h=>{d=ee(d,h)}),d},l=this.collectedTrainableWeights.map(p=>p.read()),u=!0;return[this.optimizer_.minimize(i,u,l)].concat(a)}}makeTestFunction(){this.testFunction=e=>G(()=>{let 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stopTraining(e){this.stopTraining_=e}get stopTraining(){return this.stopTraining_}get optimizer(){return this.optimizer_}set optimizer(e){this.optimizer_!==e&&(this.optimizer_=e,this.isOptimizerOwned=!1)}dispose(){let e=super.dispose();if(e.refCountAfterDispose===0&&this.optimizer!=null&&this.isOptimizerOwned){let t=qc().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-qc().numTensors}return e}getLossIdentifiers(){let e;if(typeof this.loss=="string")e=Jo(this.loss);else if(Array.isArray(this.loss)){for(let t of this.loss)if(typeof t!="string")throw new Error("Serialization of non-string loss is not supported.");e=this.loss.map(t=>Jo(t))}else{let t=Object.keys(this.loss);e={};let n=this.loss;for(let o of t)if(typeof n[o]=="string")e[o]=Jo(n[o]);else throw new Error("Serialization of non-string loss is not supported.")}return e}getMetricIdentifiers(){if(typeof this.metrics=="string"||typeof 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e.metrics)s[a]=za(e.metrics[a])}this.compile({loss:o,metrics:s,optimizer:n})}async save(e,t){if(typeof e=="string"){let u=Ir.getSaveHandlers(e);if(u.length===0)throw new z(`Cannot find any save handlers for URL '${e}'`);if(u.length>1)throw new z(`Found more than one (${u.length}) save handlers for URL '${e}'`);e=u[0]}if(e.save==null)throw new z("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await Ir.encodeWeights(this.getNamedWeights(t)),o=!1,s=null,i={modelTopology:this.toJSON(s,o),format:kQ,generatedBy:`TensorFlow.js tfjs-layers v${Wp}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){i.trainingConfig=this.getTrainingConfig();let u="optimizer",{data:c,specs:p}=await Ir.encodeWeights(await this.optimizer.getWeights(),u);n.specs.push(...p),n.data=Ir.concatenateArrayBuffers([n.data,c])}if(this.userDefinedMetadata!=null){let u=!0;PC(this.userDefinedMetadata,this.name,u),i.userDefinedMetadata=this.userDefinedMetadata}return i.weightData=n.data,i.weightSpecs=n.specs,e.save(i)}setUserDefinedMetadata(e){PC(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};Tn.className="Model";Q.registerClass(Tn);var BC=class extends Tn{};BC.className="Functional";Q.registerClass(BC);async function BL(r,e){"modelTopology"in r||(r={modelTopology:r}),r=r;let t=r.modelTopology;t.model_config!=null&&(t=t.model_config);let n=cc(t),o=Qr(n,e);if(r.weightsManifest!=null){let s=await Ir.loadWeights(r.weightsManifest,r.pathPrefix,o.weights.map(i=>i.originalName)),a={};for(let i of o.weights)a[i.originalName]=s[i.originalName];o.loadWeights(a),Ae(s)}return o}async function VL(r,e){if(e==null&&(e={}),typeof r=="string"){let t=Ir.getLoadHandlers(r,e);if(t.length===0)t.push(Ir.browserHTTPRequest(r,e));else if(t.length>1)throw new z(`Found more than one (${t.length}) load handlers for URL 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this.model.fitDataset(e,t)}async trainOnBatch(e,t){return this.model.trainOnBatch(e,t)}static fromConfig(e,t,n={},o=!1){let s,a={};if(t instanceof Array){if(t[0].className==null||t[0].className==="Merge")throw new z("Legacy serialization format not supported yet.");s=t}else y.assert(t.layers!=null,()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."),s=t.layers,delete t.layers,a=t;let i=new e(a);if(!(i instanceof qi))throw new Se(`Sequential.fromConfig called on non-Sequential input: ${i}`);for(let l of s){let c=Qr(l,void 0,o);o&&c.setFastWeightInitDuringBuild(!0),i.add(c)}return i}set stopTraining(e){if(this.model==null)throw new z("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=e}get stopTraining(){if(this.model==null)throw new z("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};qi.className="Sequential";Q.registerClass(qi);function GL(r){return new Tn(r)}function WL(r){return new qi(r)}function jL(r,e){return e==null&&(e={}),VL(r,e)}function Mx(r){return bx(r)}function UL(r,e){mn.registerCallbackConstructor(r,e)}var fn=class extends Q.Serializable{getConfig(){return{}}},VC=class extends fn{apply(e,t=1){return pL(e,t)}};VC.className="elu";Q.registerClass(VC);var GC=class extends fn{apply(e){return Ou(e)}};GC.className="selu";Q.registerClass(GC);var WC=class extends fn{apply(e){return Sr(e)}};WC.className="relu";Q.registerClass(WC);var jC=class extends fn{apply(e){return G(()=>As(6,Sr(e)))}};jC.className="relu6";Q.registerClass(jC);var UC=class extends fn{apply(e){return e}};UC.className="linear";Q.registerClass(UC);var HC=class extends fn{apply(e){return 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};cd.className="ThresholdedReLU";Q.registerClass(cd);var pd=class extends Me{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new sd().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Fe(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}};pd.className="Softmax";Q.registerClass(pd);function Il(r,e,t){if(typeof r=="number")return Zo(r,e);if(r.length!==e)throw new z(`The ${t} argument must be an integer or tuple of ${e} integers. 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Received: ${JSON.stringify(r)} including a non-integer number ${o}`)}return r}function dn(r,e,t,n,o=1){if(r==null)return r;let s=e+(e-1)*(o-1),a;return t==="same"?a=r:a=r-s+1,Math.floor((a+n-1)/n)}function md(r,e,t,n){if(r==null)return null;if(n==="valid")r=r*e+Ls([t-e,0]);else if(n==="same")r=r*e;else throw new z(`Unsupport padding mode: ${n}.`);return r}function fd(r,e){return G(()=>(Rt(e),e==="channelsFirst"?Ue(r,[0,2,3,1]):r))}function r0(r,e){return G(()=>(Rt(e),e==="channelsFirst"?Ue(r,[0,2,3,4,1]):r))}function CQ(r,e,t,n=1,o="valid",s,a=1){return G(()=>{if(s==null&&(s=Zr()),Rt(s),r.shape.length!==3)throw new z(`The input of a conv1dWithBias operation should be 3, but is ${r.shape.length} instead.`);if(e.shape.length!==3)throw new z(`The kernel for a conv1dWithBias operation should be 3, but is ${e.shape.length} instead`);if(t!=null&&t.shape.length!==1)throw new z(`The bias for a conv1dWithBias operation should be 1, but is ${e.shape.length} instead`);if(s==="channelsFirst"&&(r=Ue(r,[0,2,1])),o==="causal")throw new Se("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=_u(r,e,n,o==="same"?"same":"valid","NWC",a);return t!=null&&(i=cn(i,t)),i})}function YL(r,e,t,n=[1,1],o="valid",s,a,i=null){return G(()=>{if(s==null&&(s=Zr()),Rt(s),r.rank!==3&&r.rank!==4)throw new z(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${r.rank}.`);if(e.rank!==3&&e.rank!==4)throw new z(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${r.rank}.`);let l=fd(r,s);if(o==="causal")throw new Se("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Go.conv2d({x:l,filter:e,strides:n,pad:o==="same"?"same":"valid",dilations:a,dataFormat:"NHWC",bias:t,activation:i}),s==="channelsFirst"&&(l=Ue(l,[0,3,1,2])),l})}function IQ(r,e,t,n=[1,1,1],o="valid",s,a){return G(()=>{if(s==null&&(s=Zr()),Rt(s),r.rank!==4&&r.rank!==5)throw new z(`conv3dWithBias expects input to be of rank 4 or 5, but received ${r.rank}.`);if(e.rank!==4&&e.rank!==5)throw new z(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${r.rank}.`);let i=r0(r,s);if(o==="causal")throw new Se("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=$m(i,e,n,o==="same"?"same":"valid","NDHWC",a),t!=null&&(i=cn(i,t)),s==="channelsFirst"&&(i=Ue(i,[0,4,1,2,3])),i})}var Up=class extends Me{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Up.verifyArgs(t),this.rank=e,Ht(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Se(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Il(t.kernelSize,e,"kernelSize"),this.strides=Il(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Jr(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Rt(this.dataFormat),this.activation=Vs(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=pt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Pt(t.biasConstraint),this.biasRegularizer=wt(t.biasRegularizer),this.activityRegularizer=wt(t.activityRegularizer),this.dilationRate=Il(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new z(`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 z(`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 z(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Gn("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!ux(e.kernelSize,"number",1,3))throw new z(`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:Bs(this.activation),useBias:this.useBias,biasInitializer:vt(this.biasInitializer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),biasConstraint:Ot(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},fc=class extends Up{constructor(e,t){super(e,t);this.kernel=null,fc.verifyArgs(t),this.filters=t.filters,Ht(this.filters,"filters"),this.kernelInitializer=pt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Pt(t.kernelConstraint),this.kernelRegularizer=wt(t.kernelRegularizer)}build(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new z(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],o=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",o,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 G(()=>{e=Fe(e);let n,o=this.bias==null?null:this.bias.read(),s=cx(this.activation.getClassName());if(s!=null&&this.rank===2)n=YL(e,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)n=CQ(e,this.kernel.read(),o,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=YL(e,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=IQ(e,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Se("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=Je(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=dn(n[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);t.push(a)}let o=[e[0]];return this.dataFormat==="channelsLast"?(o=o.concat(t),o.push(this.filters)):(o.push(this.filters),o=o.concat(t)),o}getConfig(){let e={filters:this.filters,kernelInitializer:vt(this.kernelInitializer),kernelRegularizer:st(this.kernelRegularizer),kernelConstraint:Ot(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 z(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Nl=class extends fc{constructor(e){super(2,e);Nl.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!ux(e.kernelSize,"number",1,2))throw new z(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Nl.className="Conv2D";Q.registerClass(Nl);var dc=class extends fc{constructor(e){super(3,e);dc.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 z(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};dc.className="Conv3D";Q.registerClass(dc);var dd=class extends Nl{constructor(e){super(e);if(this.inputSpec=[new Tt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Je(e),e.length!==4)throw new z("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],o=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",o,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Tt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return G(()=>{let n=Fe(e);if(n.shape.length!==4)throw new z(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let o=n.shape,s=o[0],a,i;this.dataFormat==="channelsFirst"?(a=2,i=3):(a=1,i=2);let l=o[a],u=o[i],c=this.kernelSize[0],p=this.kernelSize[1],m=this.strides[0],f=this.strides[1],d=md(l,m,c,this.padding),h=md(u,f,p,this.padding),g=[s,d,h,this.filters];this.dataFormat!=="channelsLast"&&(n=Ue(n,[0,2,3,1]));let x=vu(n,this.kernel.read(),g,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(x=Ue(x,[0,3,1,2])),this.bias!=null&&(x=cn(x,this.bias.read(),this.dataFormat)),this.activation!=null&&(x=this.activation.apply(x)),x})}computeOutputShape(e){e=Je(e);let t=e.slice(),n,o,s;this.dataFormat==="channelsFirst"?(n=1,o=2,s=3):(n=3,o=1,s=2);let a=this.kernelSize[0],i=this.kernelSize[1],l=this.strides[0],u=this.strides[1];return t[n]=this.filters,t[o]=md(t[o],l,a,this.padding),t[s]=md(t[s],u,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};dd.className="Conv2DTranspose";Q.registerClass(dd);var n0=class extends fc{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 z("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new z("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 z(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=pt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=wt(t.depthwiseRegularizer),this.depthwiseConstraint=Pt(t.depthwiseConstraint),this.pointwiseInitializer=pt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=wt(t.pointwiseRegularizer),this.pointwiseConstraint=Pt(t.pointwiseConstraint)}build(e){if(e=Je(e),e.length<this.rank+2)throw new z(`Inputs to SeparableConv${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 z(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],o=this.kernelSize.concat([n,this.depthMultiplier]),s=[];for(let i=0;i<this.rank;++i)s.push(1);s.push(n*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",o,"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 Tt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return G(()=>{e=Fe(e);let n;if(this.rank===1)throw new Se("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=Ue(e,[0,2,3,1])),n=Hm(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=cn(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=Ue(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=vt(this.depthwiseInitializer),e.pointwiseInitializer=vt(this.pointwiseInitializer),e.depthwiseRegularizer=st(this.depthwiseRegularizer),e.pointwiseRegularizer=st(this.pointwiseRegularizer),e.depthwiseConstraint=Ot(this.depthwiseConstraint),e.pointwiseConstraint=Ot(this.pointwiseConstraint),e}};n0.className="SeparableConv";var hd=class extends n0{constructor(e){super(2,e)}};hd.className="SeparableConv2D";Q.registerClass(hd);var hc=class extends fc{constructor(e){super(1,e);hc.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"&&!ux(e.kernelSize,"number",1,1))throw new z(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};hc.className="Conv1D";Q.registerClass(hc);var gd=class extends Me{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 G(()=>{if(e=Fe(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}};gd.className="Cropping2D";Q.registerClass(gd);var xd=class extends Me{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,Rt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,nL(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 G(()=>{let n=Fe(e),o=n.shape;if(this.dataFormat==="channelsFirst"){n=Ue(n,[0,2,3,1]);let s=this.size[0]*o[2],a=this.size[1]*o[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([s,a]):n.resizeBilinear([s,a]);return Ue(i,[0,3,1,2])}else{let s=this.size[0]*o[1],a=this.size[1]*o[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}};xd.className="UpSampling2D";Q.registerClass(xd);function NQ(r,e,t=[1,1],n="valid",o,s){return G(()=>{o==null&&(o=Zr()),Rt(o);let a=fd(r,o);if(r.rank!==4)throw new z(`Input for depthwiseConv2d is required to be 4-D, but is instead ${r.rank}-D`);if(e.rank!==4)throw new z(`depthwiseKernel is required to be 4-D, but is instead ${e.rank}-D`);return a=Is(a,e,t,n==="same"?"same":"valid","NHWC",s),o==="channelsFirst"&&(a=Ue(a,[0,3,1,2])),a})}var yd=class extends Up{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=pt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Pt(e.depthwiseConstraint),this.depthwiseRegularizer=wt(e.depthwiseRegularizer)}build(e){if(e=Je(e),e.length<4)throw new z(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new z(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],o=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",o,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 G(()=>{e=Fe(e);let n=NQ(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=cn(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],o=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,s=dn(t,this.kernelSize[0],this.padding,this.strides[0]),a=dn(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],o,s,a]:[e[0],s,a,o]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=vt(this.depthwiseInitializer),e.depthwiseRegularizer=st(this.depthwiseRegularizer),e.depthwiseConstraint=Ot(this.depthwiseRegularizer),e}};yd.className="DepthwiseConv2D";Q.registerClass(yd);function o0(r,e,t,n){if(Array.isArray(r)){if(e!=null||t!=null)throw new z("When inputs is an array, neither initialState or constants should be provided");n!=null&&(t=r.slice(r.length-n,r.length),r=r.slice(0,r.length-n)),r.length>1&&(e=r.slice(1,r.length)),r=r[0]}function o(s){return s==null||Array.isArray(s)?s:[s]}return e=o(e),t=o(t),{inputs:r,initialState:e,constants:t}}function s0(r,e,t,n=!1,o,s,a=!1,i=!1){return G(()=>{let l=e.shape.length;if(l<3)throw new z(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(zr(2,l));if(e=Ue(e,u),s!=null)throw new Se("The rnn() functoin of the deeplearn.js backend does not support constants yet.");a&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),o!=null&&(o=o.asType("bool").asType("float32"),o.rank===l-1&&(o=ar(o,-1)),o=Ue(o,u)),n&&(e=qt(e,0),o!=null&&(o=qt(o,0)));let c=[],p,m=t,f=e.shape[0],d=pr(e),h;o!=null&&(h=pr(o));for(let x=0;x<f;++x){let w=d[x],b=G(()=>r(w,m));if(o==null)p=b[0],m=b[1];else{let k=G(()=>{let _=h[x],A=tr(_).sub(_),N=b[0].mul(_).add(m[0].mul(A)),$=m.map((F,M)=>b[1][M].mul(_).add(F.mul(A)));return{output:N,newStates:$}});p=k.output,m=k.newStates}i&&c.push(p)}let g;return i&&(g=Vt(c,1)),[p,g,m]})}var hn=class extends Me{constructor(e){super(e);let t;if(e.cell==null)throw new z("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Hp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new z("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 Tt({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 zr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){yx(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],o;if(this.returnSequences?o=[e[0],e[1],n]:o=[e[0],n],this.returnState){let s=[];for(let a of t)s.push([e[0],a]);return[o].concat(s)}else return o}computeMask(e,t){return G(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let o=this.states.map(s=>null);return[n].concat(o)}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 Se("Constants support is not implemented in RNN yet.");yx(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,o=e.slice(2);this.inputSpec[0]=new Tt({shape:[n,null,...o]});let s=[e[0]].concat(e.slice(2));if(t!=null)throw new Se("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(!y.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),a))throw new z(`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(i=>new Tt({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){G(()=>{if(!this.stateful)throw new Sn("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new z("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(o=>gt([n,o])):this.states_=[gt([n,this.cell.stateSize])];else if(e==null)Ae(this.states_),this.keptStates!=null&&(Ae(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(o=>gt([n,o])):this.states_[0]=gt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new z(`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()):Ae(this.states_);for(let o=0;o<this.states_.length;++o){let s=e[o],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[o]:this.cell.stateSize,i=[n,a];if(!y.arraysEqual(s.shape,i))throw new z(`State ${o} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${s.shape}`);this.states_[o]=s}}this.states_=this.states_.map(o=>Dt(o.clone()))})}apply(e,t){let n=t==null?null:t.initialState,o=t==null?null:t.constants;t==null&&(t={});let s=o0(e,n,o,this.numConstants);e=s.inputs,n=s.initialState,o=s.constants;let a=[],i=[];if(n!=null){t.initialState=n,a=a.concat(n),this.stateSpec=[];for(let u of n)this.stateSpec.push(new Tt({shape:u.shape}));i=i.concat(this.stateSpec)}if(o!=null&&(t.constants=o,a=a.concat(o),this.numConstants=o.length),a[0]instanceof Vr){let u=[e].concat(a),c=this.inputSpec.concat(i),p=this.inputSpec;this.inputSpec=c;let m=super.apply(u,t);return this.inputSpec=p,m}else return super.apply(e,t)}call(e,t){return G(()=>{let n=t==null?null:t.mask,o=t==null?null:t.training,s=t==null?null:t.initialState;e=Fe(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 z(`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 i={training:o},u=s0((d,h)=>{let g=this.cell.call([d].concat(h),i);return[g[0],g.slice(1)]},e,s,this.goBackwards,n,null,this.unroll,this.returnSequences),c=u[0],p=u[1],m=u[2];this.stateful&&this.resetStates(m,o);let f=this.returnSequences?p:c;return this.returnState?[f].concat(m):f})}getInitialState(e){return G(()=>{let t=gt(e.shape);return t=ge(t,[1,2]),t=Va(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?fx(t,[1,n]):t):this.cell.stateSize>1?[fx(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()===hn.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let o=t.cell,s=Qr(o,n);return new e(Object.assign(t,{cell:s}))}};hn.className="RNN";Q.registerClass(hn);var Sl=class extends Me{},qp=class extends Sl{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,Ht(this.units,"units"),this.activation=Vs(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=wt(e.kernelRegularizer),this.recurrentRegularizer=wt(e.recurrentRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.kernelConstraint=Pt(e.kernelConstraint),this.recurrentConstraint=Pt(e.recurrentConstraint),this.biasConstraint=Pt(e.biasConstraint),this.dropout=ic([1,Ls([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ic([1,Ls([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(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 G(()=>{if(e=e,e.length!==2)throw new z(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let o=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Wa({ones:()=>tr(e),rate:this.dropout,training:o})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Wa({ones:()=>tr(n),rate:this.recurrentDropout,training:o}));let s,a=this.dropoutMask,i=this.recurrentDropoutMask;a!=null?s=rs(P(e,a),this.kernel.read()):s=rs(e,this.kernel.read()),this.bias!=null&&(s=cn(s,this.bias.read())),i!=null&&(n=P(n,i));let l=ee(s,rs(n,this.recurrentKernel.read()));return this.activation!=null&&(l=this.activation.apply(l)),[l,l]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Bs(this.activation),useBias:this.useBias,kernelInitializer:vt(this.kernelInitializer),recurrentInitializer:vt(this.recurrentInitializer),biasInitializer:vt(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ot(this.kernelConstraint),recurrentConstraint:Ot(this.recurrentConstraint),biasConstraint:Ot(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};qp.className="SimpleRNNCell";Q.registerClass(qp);var bd=class extends hn{constructor(e){e.cell=new qp(e),super(e)}call(e,t){return G(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,o=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:n,training:o,initialState:s})})}static fromConfig(e,t){return new e(t)}};bd.className="SimpleRNN";Q.registerClass(bd);var Kp=class extends Sl{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 z("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Ht(this.units,"units"),this.activation=Vs(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Vs(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=wt(e.kernelRegularizer),this.recurrentRegularizer=wt(e.recurrentRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.kernelConstraint=Pt(e.kernelConstraint),this.recurrentConstraint=Pt(e.recurrentConstraint),this.biasConstraint=Pt(e.biasConstraint),this.dropout=ic([1,Ls([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ic([1,Ls([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(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 G(()=>{if(e=e,e.length!==2)throw new z(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,o=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Wa({ones:()=>tr(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Wa({ones:()=>tr(o),rate:this.recurrentDropout,training:n,count:3}));let s=this.dropoutMask,a=this.recurrentDropoutMask,i,l,u;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let c=rs(e,this.kernel.read());this.useBias&&(c=cn(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(o=P(o,a[0]));let p=this.recurrentKernel.read(),[m,f]=cr(p,[2*this.units,this.units],p.rank-1),d=rs(o,m),[h,g,x]=cr(c,3,c.rank-1),[w,b]=cr(d,2,d.rank-1);i=this.recurrentActivation.apply(ee(h,w)),l=this.recurrentActivation.apply(ee(g,b));let k=rs(P(l,o),f);u=this.activation.apply(ee(x,k));let _=ee(P(i,o),P(ee(1,He(i)),u));return[_,_]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Bs(this.activation),recurrentActivation:Bs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:vt(this.kernelInitializer),recurrentInitializer:vt(this.recurrentInitializer),biasInitializer:vt(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ot(this.kernelConstraint),recurrentConstraint:Ot(this.recurrentConstraint),biasConstraint:Ot(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};Kp.className="GRUCell";Q.registerClass(Kp);var wd=class extends hn{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Kp(e),super(e)}call(e,t){return G(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,o=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:n,training:o,initialState:s})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};wd.className="GRU";Q.registerClass(wd);var Tl=class extends Sl{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Ht(this.units,"units"),this.activation=Vs(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Vs(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=wt(e.kernelRegularizer),this.recurrentRegularizer=wt(e.recurrentRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.kernelConstraint=Pt(e.kernelConstraint),this.recurrentConstraint=Pt(e.recurrentConstraint),this.biasConstraint=Pt(e.biasConstraint),this.dropout=ic([1,Ls([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ic([1,Ls([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=Je(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let o;if(this.useBias){if(this.unitForgetBias){let s=this.biasInitializer,a=this.units;o=new(t=class extends pn{apply(l,u){let c=s.apply([a]),p=new lc().apply([a]),m=s.apply([a*2]);return AC(AC(c,p),m)}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,o,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return G(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new z(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let o=e[1],s=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Wa({ones:()=>tr(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Wa({ones:()=>tr(o),rate:this.recurrentDropout,training:n,count:4}));let a=this.dropoutMask,i=this.recurrentDropoutMask,l,u,c,p;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let m=rs(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(o=P(o,i[0])),m=ee(m,rs(o,this.recurrentKernel.read())),this.useBias&&(m=cn(m,this.bias.read()));let[f,d,h,g]=cr(m,4,m.rank-1);l=this.recurrentActivation.apply(f),u=this.recurrentActivation.apply(d),c=ee(P(u,s),P(l,this.activation.apply(h))),p=this.recurrentActivation.apply(g);let x=P(p,this.activation.apply(c));return[x,x,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Bs(this.activation),recurrentActivation:Bs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:vt(this.kernelInitializer),recurrentInitializer:vt(this.recurrentInitializer),biasInitializer:vt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ot(this.kernelConstraint),recurrentConstraint:Ot(this.recurrentConstraint),biasConstraint:Ot(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Tl.className="LSTMCell";Q.registerClass(Tl);var kd=class extends hn{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Tl(e),super(e)}call(e,t){return G(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,o=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:n,training:o,initialState:s})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};kd.className="LSTM";Q.registerClass(kd);var Hp=class extends Sl{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return G(()=>{e=e;let n=e.slice(1),o=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?o.push(n.splice(0,i.stateSize.length)):o.push(n.splice(0,1));o.reverse();let s=[],a;for(let i=0;i<this.cells.length;++i){let l=this.cells[i];n=o[i],i===0?a=[e[0]].concat(n):a=[a[0]].concat(n),a=l.call(a,t),s.push(a.slice(1))}n=[];for(let i of s.slice().reverse())n.push(...i);return[a[0]].concat(n)})}build(e){yx(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,o)=>{Ms(`RNNCell_${o}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=s=>({className:s.getClassName(),config:s.getConfig()}),o={cells:this.cells.map(t)};return Object.assign({},e,o)}static fromConfig(e,t,n={}){let o=[];for(let s of t.cells)o.push(Qr(s,n));return new e({cells:o})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return Zf(e)}setWeights(e){let t=[];for(let n of this.cells){let o=n.weights.length,s=e.splice(o);for(let a=0;a<n.weights.length;++a)t.push([n.weights[a],s[a]])}zp(t)}};Hp.className="StackedRNNCells";Q.registerClass(Hp);function Wa(r){let{ones:e,rate:t,training:n=!1,count:o=1}=r,s=()=>hx(e(),t),a=()=>bl(s,e,n);return!o||o<=1?Dt(a().clone()):Array(o).fill(void 0).map(a).map(l=>Dt(l.clone()))}var SQ=function(r,e){var t={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&e.indexOf(n)<0&&(t[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var o=0,n=Object.getOwnPropertySymbols(r);o<n.length;o++)e.indexOf(n[o])<0&&Object.prototype.propertyIsEnumerable.call(r,n[o])&&(t[n[o]]=r[n[o]]);return t};var i0=class extends hn{constructor(e){if(e.unroll)throw new Se("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Se("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Tt({ndim:5})]}call(e,t){return G(()=>{if(this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new z("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,o=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:n,training:o,initialState:s})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return G(()=>{let{stateSize:t}=this.cell,n=e.shape,o=this.computeSingleOutputShape(n),s=[o[0],...o.slice(2)],a=gt(s);return Array.isArray(t)?Array(t.length).fill(a):[a]})}resetStates(e,t=!1){G(()=>{if(!this.stateful)throw new Sn("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,o=this.computeSingleOutputShape(n),s=[o[0],...o.slice(2)];if(n[0]==null)throw new z("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>gt(s)):this.states_=[gt(s)];else if(e==null)Ae(this.states_),this.keptStates!=null&&(Ae(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>gt(s)):this.states_[0]=gt(s);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new z(`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()):Ae(this.states_);for(let i=0;i<this.states_.length;++i){let l=e[i],u=s;if(!y.arraysEqual(l.shape,u))throw new z(`State ${i} is incompatible with layer ${this.name}: expected shape=${u}, received shape=${l.shape}`);this.states_[i]=l}}this.states_=this.states_.map(i=>Dt(i.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:o,padding:s,strides:a,dilationRate:i}=this.cell,l=t==="channelsFirst",u=e[l?3:2],c=e[l?4:3],p=dn(u,o[0],s,a[0],i[0]),m=dn(c,o[1],s,a[1],i[1]);return[...e.slice(0,2),...l?[n,p,m]:[p,m,n]]}};i0.className="ConvRNN2D";var Xp=class extends Tl{constructor(e){let{filters:t,kernelSize:n,strides:o,padding:s,dataFormat:a,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Ht(this.filters,"filters"),this.kernelSize=Il(n,2,"kernelSize"),this.kernelSize.forEach(l=>Ht(l,"kernelSize")),this.strides=Il(o||1,2,"strides"),this.strides.forEach(l=>Ht(l,"strides")),this.padding=s||"valid",Jr(this.padding),this.dataFormat=a||"channelsLast",Rt(this.dataFormat),this.dilationRate=Il(i||1,2,"dilationRate"),this.dilationRate.forEach(l=>Ht(l,"dilationRate"))}build(e){var t;e=Je(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new z(`The channel dimension of the input should be defined. Found ${e[n]}`);let o=e[n],s=4,a=this.kernelSize.concat([o,this.filters*s]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*s]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let l;if(this.unitForgetBias){let u=this.biasInitializer,c=this.filters;l=new(t=class extends pn{apply(m,f){let d=u.apply([c]),h=Nr([c]),g=u.apply([c*2]);return Ap([d,h,g])}},t.className="CustomInit",t)}else l=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*s],null,l,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return G(()=>{if(e.length!==3)throw new z(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,o=e[0],s=e[1],a=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Wa({ones:()=>tr(o),rate:this.dropout,training:n,count:i}));let l=this.dropoutMask,u=(J,ie,ue)=>!ie||!ie[ue]?J:P(ie[ue],J),c=u(o,l,0),p=u(o,l,1),m=u(o,l,2),f=u(o,l,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Wa({ones:()=>tr(s),rate:this.recurrentDropout,training:n,count:i}));let d=this.recurrentDropoutMask,h=u(s,d,0),g=u(s,d,1),x=u(s,d,2),w=u(s,d,3),b=3,[k,_,A,N]=cr(this.kernel.read(),i,b),[$,F,M,V]=this.useBias?cr(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,k,$,this.padding),p=this.inputConv(p,_,F,this.padding),m=this.inputConv(m,A,M,this.padding),f=this.inputConv(f,N,V,this.padding);let[W,U,H,q]=cr(this.recurrentKernel.read(),i,b);h=this.recurrentConv(h,W),g=this.recurrentConv(g,U),x=this.recurrentConv(x,H),w=this.recurrentConv(w,q);let X=this.recurrentActivation.apply(ee(c,h)),ne=this.recurrentActivation.apply(ee(p,g)),Y=ee(P(ne,a),P(X,this.activation.apply(ee(m,x)))),re=P(this.recurrentActivation.apply(ee(f,w)),this.activation.apply(Y));return[re,re,Y]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=SQ(e,["units"]),o={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,o)}inputConv(e,t,n,o){let s=Kr(e,t,this.strides,o||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?cn(s,n,this.dataFormat):s}recurrentConv(e,t){return Kr(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Xp.className="ConvLSTM2DCell";Q.registerClass(Xp);var _d=class extends i0{constructor(e){let t=new Xp(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};_d.className="ConvLSTM2D";Q.registerClass(_d);var Yp=class extends Me{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 o=0;o<this.noiseShape.length;++o)n.push(this.noiseShape[o]==null?t[o]:this.noiseShape[o]);return n}call(e,t){return G(()=>{this.invokeCallHook(e,t);let n=Fe(e);if(0<this.rate&&this.rate<1){let o=t.training==null?!1:t.training,s=this.getNoiseShape(n);return bl(()=>hx(n,this.rate,s,this.seed),()=>n,o)}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()}};Yp.className="Dropout";Q.registerClass(Yp);var vd=class extends Yp{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};vd.className="SpatialDropout1D";Q.registerClass(vd);var Cd=class extends Me{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,Ht(this.units,"units"),this.activation=Vs(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Pt(e.kernelConstraint),this.biasConstraint=Pt(e.biasConstraint),this.kernelRegularizer=wt(e.kernelRegularizer),this.biasRegularizer=wt(e.biasRegularizer),this.activityRegularizer=wt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=Je(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=Je(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return G(()=>{this.invokeCallHook(e,t);let n=Fe(e),o=cx(this.activation.getClassName()),s;return o!=null?s=rs(n,this.kernel.read(),o,this.bias?this.bias.read():null):(s=rs(n,this.kernel.read()),this.bias!=null&&(s=cn(s,this.bias.read())),this.activation!=null&&(s=this.activation.apply(s))),s})}getConfig(){let e={units:this.units,activation:Bs(this.activation),useBias:this.useBias,kernelInitializer:vt(this.kernelInitializer),biasInitializer:vt(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ot(this.kernelConstraint),biasConstraint:Ot(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Cd.className="Dense";Q.registerClass(Cd);var Id=class extends Me{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=Je(e);for(let t of e.slice(1))if(t==null)throw new z(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],ts(e,1)]}call(e,t){return G(()=>{this.invokeCallHook(e,t);let n=Fe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let o=[0];for(let s=2;s<n.rank;++s)o.push(s);o.push(1),n=n.transpose(o)}return cL(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};Id.className="Flatten";Q.registerClass(Id);var Nd=class extends Me{constructor(e){super(e);this.supportsMasking=!0,this.activation=Vs(e.activation)}call(e,t){return G(()=>{this.invokeCallHook(e,t);let n=Fe(e);return this.activation.apply(n)})}getConfig(){let e={activation:Bs(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Nd.className="Activation";Q.registerClass(Nd);var Sd=class extends Me{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return G(()=>(e=Fe(e),lL(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Sd.className="RepeatVector";Q.registerClass(Sd);var Td=class extends Me{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.",o=t.slice(),s=1,a=null;for(let l=0;l<o.length;++l){let u=o[l];if(this.isUnknown(u))if(a===null)a=l;else throw new z("Can only specifiy one unknown dimension.");else s*=u}let i=ts(e);if(a!==null){if(s===0||i%s!=0)throw new z(n);o[a]=i/s}else if(i!==s)throw new z(n);return o}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 G(()=>{this.invokeCallHook(e,t);let n=Fe(e),o=n.shape,s=o.slice(0,1).concat(this.fixUnknownDimension(o.slice(1),this.targetShape));return n.reshape(s)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Td.className="Reshape";Q.registerClass(Td);var Ad=class extends Me{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=zr(1,e.dims.length+1);if(!y.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 Tt({ndim:this.dims.length+1})]}computeOutputShape(e){e=Je(e);let t=e.slice();return this.dims.forEach((n,o)=>{t[o+1]=e[n]}),t}call(e,t){return Ue(Fe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Ad.className="Permute";Q.registerClass(Ad);var Ed=class extends Me{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Fe(e),o=-1;return sl(Vo(n,this.maskValue),o)}call(e,t){return G(()=>{this.invokeCallHook(e,t);let n=Fe(e),o=-1,s=!0,a=sl(Vo(n,this.maskValue),o,s);return n.mul(a.asType(n.dtype))})}};Ed.className="Masking";Q.registerClass(Ed);var Dd=class extends Me{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(bt(e.inputLength))}this.inputDim=e.inputDim,Ht(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Ht(this.outputDim,"outputDim"),this.embeddingsInitializer=pt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=wt(e.embeddingsRegularizer),this.activityRegularizer=wt(e.activityRegularizer),this.embeddingsConstraint=Pt(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return G(()=>this.maskZero?(e=Fe(e),Vo(e,Ce(e))):null)}computeOutputShape(e){if(e=Je(e),this.inputLength==null)return[...e,this.outputDim];let t=bt(this.inputLength);if(t.length!==e.length-1)throw new z(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let o=0;o<t.length;++o){let s=t[o],a=e[o+1];if(s!=null&&a!=null&&s!==a)throw new z(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);s==null&&(t[n]=a),n++}}return[e[0],...t,this.outputDim]}call(e,t){return G(()=>{this.invokeCallHook(e,t);let n=Fe(e);return n.dtype!=="int32"&&(n=Ba(n,"int32")),dx(this.embeddings.read(),n.as1D()).reshape(Je(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:vt(this.embeddingsInitializer),embeddingsRegularizer:st(this.embeddingsRegularizer),activityRegularizer:st(this.activityRegularizer),embeddingsConstraint:Ot(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Dd.className="Embedding";Q.registerClass(Dd);var Al=class extends Me{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new Se}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let o=0;o<t.length;++o){let s=e[e.length-t.length+o],a=t[o];if(s==null||a==null||s<0||a<0)n.push(null);else if(s===1)n.push(a);else if(a===1)n.push(s);else{if(s!==a)throw new z("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(s)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[Je(e)]),e=e,e.length<2)throw new z(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let s of e)s!=null&&s[0]!==null&&t.push(s[0]);if(t=es(t),t.length>1)throw new z(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let s=1;s<e.length;++s){let a=e[s]==null?null:e[s].slice(1);n=this.computeElementwiseOpOutputShape(n,a)}let o=e.map(s=>s.length);e.indexOf(null)===-1&&es(o).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return G(()=>{if(e=e,this.reshapeRequired){let n=[],o=e.map(s=>s.rank);if(o.indexOf(null)===-1){let s=Ls(o);for(let a of e){let i=a.rank;for(let l=0;l<s-i;++l)a=Va(a,1);n.push(a)}return this.mergeFunction(n)}else{let s=!1;for(let l of e){let u=l.rank;if(u==null){let c=l.shape,p=c[0],m=c.slice(1).concat([p]),f=l.reshape([p].concat(ts(c.slice(1))));f=Ue(f,[1,0]),f=f.reshape(m),n.push(f),s=!0}else if(u>1){let c=zr(1,u).concat([0]);n.push(Ue(l,c)),s=!0}else n.push(l)}let a=this.mergeFunction(n),i=a.rank;if(s){if(i==null){let l=a.shape,u=l.length,c=l[u-1],p=[c].concat(l.slice(0,l.length-1));a=Ue(a.reshape([-1,c]),[1,0]).reshape(p)}else if(i>1){let l=[i-1].concat(zr(0,i-1));a=Ue(a,l)}}return a}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let o=1;o<e.length;++o){let s=e[o]==null?null:e[o].slice(1);t=this.computeElementwiseOpOutputShape(t,s)}let n=[];for(let o of e)o!=null&&o[0]!==null&&n.push(o[0]);return n=es(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return G(()=>{if(t==null)return null;if(!Array.isArray(t))throw new z("`mask` should be an Array");if(!Array.isArray(e))throw new z("`inputs` should be an Array");if(t.length!==e.length)throw new z(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(o=>o==null))return null;t=t.map(o=>o==null?o:ar(o,0));let n=t[0];for(let o=1;o<t.length-1;++o)n=hr(n,t[o]);return n})}},$d=class extends Al{constructor(e){super(e)}mergeFunction(e){return G(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ee(t,e[n]);return t})}};$d.className="Add";Q.registerClass($d);var Rd=class extends Al{constructor(e){super(e)}mergeFunction(e){return G(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=P(t,e[n]);return t})}};Rd.className="Multiply";Q.registerClass(Rd);var Fd=class extends Al{constructor(e){super(e)}mergeFunction(e){return G(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ee(t,e[n]);return P(1/e.length,t)})}};Fd.className="Average";Q.registerClass(Fd);var Od=class extends Al{constructor(e){super(e)}mergeFunction(e){return G(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Yr(t,e[n]);return t})}};Od.className="Maximum";Q.registerClass(Od);var Pd=class extends Al{constructor(e){super(e)}mergeFunction(e){return G(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=As(t,e[n]);return t})}};Pd.className="Minimum";Q.registerClass(Pd);var Md=class extends Al{constructor(e){super(e);this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new z("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let o of e)if(o!=null){t=!1;break}if(t)return;let n=[];for(let o=0;o<e.length;++o){let s=e[o].slice();s.splice(this.axis,1);let a=!1;for(let i of n)if(y.arraysEqual(i,s)){a=!0;break}a||n.push(s)}if(n.length>1)throw new z("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return G(()=>Ap(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new z("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),o=this.axis<0?n.length+this.axis:this.axis;for(let s of t.slice(1)){if(n[o]==null||s[o]==null){n[o]=null;break}n[o]+=s[o]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new z("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new z("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new z(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return G(()=>{let n=!0;if(t.forEach(a=>{if(a!=null){n=!1;return}}),n)return null;let o=[];for(let a=0;a<e.length;++a)t[a]==null?o.push(tr(e[a]).asType("bool")):t[a].rank<e[a].rank?o.push(ar(t[a],-1)):o.push(t[a]);let s=Ze(o,this.axis);return bu(s,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Md.className="Concatenate";Q.registerClass(Md);function Ld(r,e){for(;r<0;)r+=e;return r}function TQ(r,e,t){if(r.shape.length>3||e.shape.length>3)throw new Se("batchDot is not implemented for tensors of 4D or higher rank yet");if(y.assert(r.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${r.shape.length}`),y.assert(r.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${e.shape.length}`),typeof t=="number"&&(t=[t,t]),r.dtype==="complex64"||e.dtype==="complex64")throw new Se("batchDot is not implemented for complex64-type Tensors yet.");let n=r.shape.length,o=e.shape.length;t==null&&(t=[n-1,o-2]);let s=t;return G(()=>{let a;if(n>o){a=n-o;let l=[];for(let u=0;u<a;++u)l.push(1);e=e.reshape(e.shape.concat(l))}else if(o>n){a=o-n;let l=[];for(let u=0;u<a;++u)l.push(1);r=r.reshape(r.shape.concat(l))}else a=0;let i;if(r.shape.length===2&&e.shape.length===2)s[0]===s[1]?i=r.mul(e).sum(s[0]):i=r.transpose([1,0]).mul(e).sum(s[1]);else{let l=s[0]!==r.shape.length-1,u=s[1]===e.shape.length-1;i=r.matMul(e,l,u)}if(a>0){let l;n>o?l=n+o-3:l=n-1;let u=[];for(let c=l;c<l+a;++c)u.push(c);i=i.squeeze(u)}return i.shape.length===1&&(i=i.expandDims(1)),i})}var zd=class extends Al{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){y.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 Se("Dot layer does not support tensors of 4D or higher rank yet.");let o=this.interpretAxes(t,n);if(t[o[0]]!==n[o[1]])throw new z(`Dimension incompatibility: ${t[o[0]]} !== ${n[o[1]]}`)}mergeFunction(e){if(e.length!==2)throw new z(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],o;return Array.isArray(this.axes)?o=this.axes.map((s,a)=>Ld(s,e[a].shape.length)):o=[Ld(this.axes,t.shape.length),Ld(this.axes,n.shape.length)],this.normalize&&(t=Jf(t,o[0]),n=Jf(n,o[1])),TQ(t,n,o)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Ld(this.axes,e.length),Ld(this.axes,t.length)],n}computeOutputShape(e){y.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new Se("Dot layer does not support tensors of 4D or higher rank yet.");let o=this.interpretAxes(t,n);t.splice(o[0],1),n.splice(o[1],1),n.splice(0,1);let s=t.concat(n);return s.length===1&&s.push(1),s}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};zd.className="Dot";Q.registerClass(zd);var Bd=class extends Me{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 G(()=>{this.invokeCallHook(e,t);let n=Fe(e);return bl(()=>Ep(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};Bd.className="GaussianNoise";Q.registerClass(Bd);var Vd=class extends Me{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 G(()=>{this.invokeCallHook(e,t);let n=Fe(e);return this.rate>0&&this.rate<1?bl(()=>{let s=Math.sqrt(this.rate/(1-this.rate));return n.mul(Ep(n.shape,1,s))},()=>n,t.training||!1):n})}};Vd.className="GaussianDropout";Q.registerClass(Vd);var Gd=class extends Me{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Fe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return G(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return bl(()=>{let s=Fe(e),a=1.6732632423543772,i=1.0507009873554805,l=-a*i,u=an(Es(n),this.rate);u=Ba(u,"float32");let c=((1-this.rate)*(1+this.rate*l**2))**-.5,p=-c*l*this.rate;return s.mul(u).add(u.add(-1).mul(l)).mul(c).add(p)},()=>Fe(e),t.training||!1)}return e})}};Gd.className="AlphaDropout";Q.registerClass(Gd);function Wd(r,e,t,n,o,s=.001){let a;if(r.rank===2)a=ww(r,e,t,n,o,s);else if(r.rank===3)a=kw(r,e,t,n,o,s);else if(r.rank===4)a=_w(r,e,t,n,o,s);else throw new Se(`batchNormalization is not implemented for array of rank ${r.rank} yet`);return a}function AQ(r,e,t,n,o=.001){return G(()=>{let s=Zc(r,n),a=s.mean,i=s.variance;return[Wd(r,a,i,t,e,o),a,i]})}function EQ(r,e,t,n,o=.001){return G(()=>{let s=Zc(r,n),a=s.mean,i=s.variance,l=[];for(let d of zr(0,r.rank))n.indexOf(d)!==-1?l.push(1):l.push(r.shape[d]);let u=a.reshape(l),c=i.reshape(l),p=e==null?null:e.reshape(l),m=t==null?null:t.reshape(l);return[Wd(r,u,c,m,p,o),a,i]})}function DQ(r,e,t,n,o=.001){return y.arraysEqual(n.slice().sort(),zr(0,r.rank-1))?AQ(r,e,t,n,o):EQ(r,e,t,n,o)}var jd=class extends Me{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=pt(e.betaInitializer||"zeros"),this.gammaInitializer=pt(e.gammaInitializer||"ones"),this.movingMeanInitializer=pt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=pt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Pt(e.betaConstraint),this.gammaConstraint=Pt(e.gammaConstraint),this.betaRegularizer=wt(e.betaRegularizer),this.gammaRegularizer=wt(e.gammaRegularizer)}build(e){e=Je(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new z(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Tt({ndim:e.length,axes:{[t]:n}})];let o=[n];this.scale&&(this.gamma=this.addWeight("gamma",o,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",o,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",o,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",o,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return G(()=>{let n=t.training==null?!1:t.training,o=Fe(e),s=o.shape,a=s.length,i=zr(0,a),l=this.axis>=0?this.axis:this.axis+a;i.splice(l,1);let u=Zo(1,a);u[l]=s[l];let c=i.slice();c.sort();let p=!y.arraysEqual(c,zr(0,a).slice(0,a-1)),m=()=>{if(p){let w=this.movingMean.read().reshape(u),b=this.movingVariance.read().reshape(u),k=this.center?this.beta.read().reshape(u):null,_=this.scale?this.gamma.read().reshape(u):null;return Wd(o,w,b,k,_,this.epsilon)}else return Wd(o,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return m();let[f,d,h]=DQ(o,this.gamma.read(),this.beta.read(),i,this.epsilon),g=(w,b,k)=>{G(()=>{let _=1-k,A=w.read(),N=A.sub(b).mul(_);w.write(A.sub(N))})};return(()=>{g(this.movingMean,d,this.momentum),g(this.movingVariance,h,this.momentum)})(),f})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:vt(this.betaInitializer),gammaInitializer:vt(this.gammaInitializer),movingMeanInitializer:vt(this.movingMeanInitializer),movingVarianceInitializer:vt(this.movingVarianceInitializer),betaRegularizer:st(this.betaRegularizer),gammaRegularizer:st(this.gammaRegularizer),betaConstraint:Ot(this.betaConstraint),gammaConstraint:Ot(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};jd.className="BatchNormalization";Q.registerClass(jd);var Ud=class extends Me{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=pt(e.betaInitializer||"zeros"),this.gammaInitializer=pt(e.gammaInitializer||"ones"),this.betaRegularizer=wt(e.betaRegularizer),this.gammaRegularizer=wt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=Je(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let s=0;s<this.axis.length;++s)this.axis[s]<0&&(this.axis[s]+=t);for(let s of this.axis)if(s<0||s>=t)throw new Error(`Invalid axis: ${s}`);if(this.axis.length!==es(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(s=>e[s]),o=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,o):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,o):this.beta=null,this.built=!0}call(e,t){let n=Fe(e),o=n.shape,s=o.length;return G(()=>{let a=!0,{mean:i,variance:l}=Zc(n,this.axis,a),u=Zo(1,s);for(let h of this.axis)u[h]=o[h];let c=h=>h!=null&&h.shape.length!==s&&this.axis!==[s-1]?h.reshape(u):h,p=c(this.gamma.read()),m=c(this.beta.read()),f=[],d=[];for(let h=0;h<s;++h)this.axis.indexOf(h)!==-1?(f.push(o[h]),d.push(1)):(f.push(1),d.push(o[h]));return i=i.tile(f),l=l.tile(f),p=p.tile(d),m=m.tile(d),Wd(n,i,l,m,p,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:vt(this.betaInitializer),gammaInitializer:vt(this.gammaInitializer),betaRegularizer:st(this.betaRegularizer),gammaRegularizer:st(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};Ud.className="LayerNormalization";Q.registerClass(Ud);function $Q(r,e,t){return G(()=>{if(r.rank!==4)throw new z(`temporalPadding expects input tensor to be 4-D, but received a ${r.rank}-D tensor.`);if(e==null&&(e=[[1,1],[1,1]]),e.length!==2||e[0].length!==2||e[1].length!==2)throw new z("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(t==null&&(t=Zr()),t!=="channelsLast"&&t!=="channelsFirst")throw new z(`Unknown data format: ${t}. 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length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Tt({ndim:4})]}computeOutputShape(e){e=Je(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return G(()=>$Q(Fe(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Hd.className="ZeroPadding2D";Q.registerClass(Hd);function Lx(r,e,t,n,o,s){return G(()=>{Rt(o),SC(s),Jr(n),t==null&&(t=[1,1]),n==null&&(n="valid"),o==null&&(o=Zr()),s==null&&(s="max"),r=fd(r,o);let a,i=n==="same"?"same":"valid";return s==="max"?a=Na(r,e,t,i):a=wa(r,e,t,i),o==="channelsFirst"&&(a=Ue(a,[0,3,1,2])),a})}function ZL(r,e,t,n,o,s){return G(()=>{Rt(o),SC(s),Jr(n),t==null&&(t=[1,1,1]),n==null&&(n="valid"),o==null&&(o=Zr()),s==null&&(s="max"),r=r0(r,o);let a,i=n==="same"?"same":"valid";return s==="max"?a=Vm(r,e,t,i):a=Em(r,e,t,i),o==="channelsFirst"&&(a=Ue(a,[0,4,1,2,3])),a})}var a0=class extends Me{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new z(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Ht(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new z(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Jr(this.padding),this.inputSpec=[new Tt({ndim:3})]}computeOutputShape(e){e=Je(e);let t=dn(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return G(()=>{this.invokeCallHook(e,t),e=Va(Fe(e),2);let n=this.poolingFunction(Fe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Cn(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},qd=class extends a0{constructor(e){super(e)}poolingFunction(e,t,n,o,s){return Rt(s),Jr(o),Lx(e,t,n,o,s,"max")}};qd.className="MaxPooling1D";Q.registerClass(qd);var Kd=class extends a0{constructor(e){super(e)}poolingFunction(e,t,n,o,s){return Rt(s),Jr(o),Lx(e,t,n,o,s,"avg")}};Kd.className="AveragePooling1D";Q.registerClass(Kd);var l0=class extends Me{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new z(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Ht(this.poolSize,"poolSize"),Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Rt(this.dataFormat),Jr(this.padding),this.inputSpec=[new Tt({ndim:4})]}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=dn(t,this.poolSize[0],this.padding,this.strides[0]),n=dn(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return G(()=>(this.invokeCallHook(e,t),this.poolingFunction(Fe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Xd=class extends l0{constructor(e){super(e)}poolingFunction(e,t,n,o,s){return Rt(s),Jr(o),Lx(e,t,n,o,s,"max")}};Xd.className="MaxPooling2D";Q.registerClass(Xd);var Yd=class extends l0{constructor(e){super(e)}poolingFunction(e,t,n,o,s){return Rt(s),Jr(o),Lx(e,t,n,o,s,"avg")}};Yd.className="AveragePooling2D";Q.registerClass(Yd);var u0=class extends Me{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new z(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Ht(this.poolSize,"poolSize"),Ht(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Rt(this.dataFormat),Jr(this.padding),this.inputSpec=[new Tt({ndim:5})]}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],o=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=dn(t,this.poolSize[0],this.padding,this.strides[0]),n=dn(n,this.poolSize[1],this.padding,this.strides[1]),o=dn(o,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,o]:[e[0],t,n,o,e[4]]}call(e,t){return G(()=>(this.invokeCallHook(e,t),this.poolingFunction(Fe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Zd=class extends u0{constructor(e){super(e)}poolingFunction(e,t,n,o,s){return Rt(s),Jr(o),ZL(e,t,n,o,s,"max")}};Zd.className="MaxPooling3D";Q.registerClass(Zd);var Jd=class extends u0{constructor(e){super(e)}poolingFunction(e,t,n,o,s){return Rt(s),Jr(o),ZL(e,t,n,o,s,"avg")}};Jd.className="AveragePooling3D";Q.registerClass(Jd);var c0=class extends Me{constructor(e){super(e);this.inputSpec=[new Tt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Se}},Qd=class extends c0{constructor(e){super(e||{})}call(e,t){return G(()=>{let n=Fe(e);return ht(n,1)})}};Qd.className="GlobalAveragePooling1D";Q.registerClass(Qd);var eh=class extends c0{constructor(e){super(e||{})}call(e,t){return G(()=>{let n=Fe(e);return ur(n,1)})}};eh.className="GlobalMaxPooling1D";Q.registerClass(eh);var p0=class extends Me{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Rt(this.dataFormat),this.inputSpec=[new Tt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Se}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},th=class extends p0{call(e,t){return G(()=>{let n=Fe(e);return this.dataFormat==="channelsLast"?ht(n,[1,2]):ht(n,[2,3])})}};th.className="GlobalAveragePooling2D";Q.registerClass(th);var rh=class extends p0{call(e,t){return G(()=>{let n=Fe(e);return this.dataFormat==="channelsLast"?ur(n,[1,2]):ur(n,[2,3])})}};rh.className="GlobalMaxPooling2D";Q.registerClass(rh);var m0=class extends Me{constructor(e){super(e);this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let o=t.layer,s=Qr(o,n);delete t.layer;let a={layer:s};return Object.assign(a,t),new e(a)}},nh=class extends m0{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=Je(e),e.length<3)throw new z(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=Je(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),o=e[1];return[n[0],o].concat(n.slice(1))}call(e,t){return G(()=>(e=Fe(e),s0((a,i)=>[Fe(this.layer.call(a,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};nh.className="TimeDistributed";Q.registerClass(nh);function RQ(r){Wi(rL,"BidirectionalMergeMode",r)}var FQ="concat",oh=class extends m0{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Qr(n),t.goBackwards=t.goBackwards!==!0;let o={};if(o.className=e.layer.getClassName(),o.config=t,this.backwardLayer=Qr(o),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?FQ:e.mergeMode,RQ(this.mergeMode),e.weights)throw new Se("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,o,s;return this.returnState&&(s=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,o=[n]):this.mergeMode==null?o=[n,n.slice()]:o=[n],this.returnState?this.mergeMode==null?o.concat(s).concat(s.slice()):[n].concat(s).concat(s.slice()):xr(o)}apply(e,t){let n=t==null?null:t.initialState,o=t==null?null:t.constants;t==null&&(t={});let s=o0(e,n,o,this.numConstants);if(e=s.inputs,n=s.initialState,o=s.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&o==null)return super.apply(e,t);let a=[],i=[];if(n!=null){let u=n.length;if(u%2>0)throw new z("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,a.push(...n);let c=n.map(p=>new 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Provided ${t} not understood: ${JSON.stringify(r)}`)}function Ax(r,e){return PJ(r,e,"classWeight")}async function Ex(r,e,t,o){if(e!=null||o!=null)throw new Error("Support sampleWeight is not implemented yet");if(t!=null){let n=V(()=>{if(r.shape.length===1)return r.clone();if(r.shape.length===2)if(r.shape[1]>1){let i=1;return r.argMax(i)}else{if(r.shape[1]===1)return r.reshape([r.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${r.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${r.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await n.data());Ae(n);let a=[];return s.forEach(i=>{if(t[i]==null)throw new Error(`classWeight must contain all classes in the training data. 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(Expected output keys: ${JSON.stringify(r.outputNames)})`);for(let l=0;l<s.length;l++)y.assert(s[l].shape[0]===i,()=>`Batch size mismatch: input ${r.inputNames[l]} has ${s[l].shape[0]}; expected  ${i} based on input ${r.inputNames[0]}.`);for(let l=0;l<a.length;l++)y.assert(a[l].shape[0]===i,()=>`Batch size mismatch: output ${r.outputNames[l]} has ${a[l].shape[0]}; expected  ${i} based on input ${r.inputNames[0]}.`);return{xs:s,ys:a}}function lL(r,e,t){if(t instanceof Ve)return[t];if(Array.isArray(t))return y.assert(t.length===e.length,()=>`Received an array of ${t.length} Tensors, but expected ${e.length} to match the ${r} keys ${e}.`),t;{let o=[];for(let n of e){if(t[n]==null)throw new z(`The feature data generated by the dataset lacks the required ${r} key '${n}'.`);o.push(t[n])}return o}}function LJ(r){if(r.length===3)throw new Se("Validation with sample weights is not implemented yet.");return{xs:r[0],ys:r[1]}}async function pL(r,e,t){let o=t.batchesPerEpoch!=null;if(y.assert(r.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),y.assert(t!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),y.assert(t.epochs!=null&&t.epochs>0&&Number.isInteger(t.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${t.epochs}`),y.assert(!o||t.batchesPerEpoch>0&&Number.isInteger(t.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${t.batchesPerEpoch}`),y.assert(t.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};ud.className="ThresholdedReLU";Q.registerClass(ud);var cd=class extends Me{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new nd().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let o=Fe(e);return this.softmax(o,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};cd.className="Softmax";Q.registerClass(cd);function Il(r,e,t){if(typeof r=="number")return Zn(r,e);if(r.length!==e)throw new z(`The ${t} argument must be an integer or tuple of ${e} integers. 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instead`);if(s==="channelsFirst"&&(r=Ue(r,[0,2,1])),n==="causal")throw new Se("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=_u(r,e,o,n==="same"?"same":"valid","NWC",a);return t!=null&&(i=uo(i,t)),i})}function SL(r,e,t,o=[1,1],n="valid",s,a,i=null){return V(()=>{if(s==null&&(s=Zr()),$t(s),r.rank!==3&&r.rank!==4)throw new z(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${r.rank}.`);if(e.rank!==3&&e.rank!==4)throw new z(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${r.rank}.`);let l=md(r,s);if(n==="causal")throw new Se("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Gn.conv2d({x:l,filter:e,strides:o,pad:n==="same"?"same":"valid",dilations:a,dataFormat:"NHWC",bias:t,activation:i}),s==="channelsFirst"&&(l=Ue(l,[0,3,1,2])),l})}function YJ(r,e,t,o=[1,1,1],n="valid",s,a){return V(()=>{if(s==null&&(s=Zr()),$t(s),r.rank!==4&&r.rank!==5)throw new z(`conv3dWithBias expects input to be of rank 4 or 5, but received ${r.rank}.`);if(e.rank!==4&&e.rank!==5)throw new z(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${r.rank}.`);let i=XC(r,s);if(n==="causal")throw new Se("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=Dm(i,e,o,n==="same"?"same":"valid","NDHWC",a),t!=null&&(i=uo(i,t)),s==="channelsFirst"&&(i=Ue(i,[0,4,1,2,3])),i})}var jp=class extends Me{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",jp.verifyArgs(t),this.rank=e,Ut(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Se(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Il(t.kernelSize,e,"kernelSize"),this.strides=Il(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Jr(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,$t(this.dataFormat),this.activation=Vs(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=pt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Ot(t.biasConstraint),this.biasRegularizer=bt(t.biasRegularizer),this.activityRegularizer=bt(t.activityRegularizer),this.dilationRate=Il(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new z(`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 z(`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 z(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Go("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!ix(e.kernelSize,"number",1,3))throw new z(`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:Bs(this.activation),useBias:this.useBias,biasInitializer:_t(this.biasInitializer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),biasConstraint:Ft(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},mc=class extends jp{constructor(e,t){super(e,t);this.kernel=null,mc.verifyArgs(t),this.filters=t.filters,Ut(this.filters,"filters"),this.kernelInitializer=pt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Ot(t.kernelConstraint),this.kernelRegularizer=bt(t.kernelRegularizer)}build(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new z(`The channel dimension of the input should be defined. Found ${e[t]}`);let o=e[t],n=this.kernelSize.concat([o,this.filters]);this.kernel=this.addWeight("kernel",n,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]:o}}],this.built=!0}call(e,t){return V(()=>{e=Fe(e);let o,n=this.bias==null?null:this.bias.read(),s=ax(this.activation.getClassName());if(s!=null&&this.rank===2)o=SL(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)o=XJ(e,this.kernel.read(),n,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)o=SL(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)o=YJ(e,this.kernel.read(),n,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Se("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(o=this.activation.apply(o))}return o})}computeOutputShape(e){e=Je(e);let t=[],o=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let s=0;s<o.length;++s){let a=fo(o[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);t.push(a)}let n=[e[0]];return this.dataFormat==="channelsLast"?(n=n.concat(t),n.push(this.filters)):(n.push(this.filters),n=n.concat(t)),n}getConfig(){let e={filters:this.filters,kernelInitializer:_t(this.kernelInitializer),kernelRegularizer:st(this.kernelRegularizer),kernelConstraint:Ft(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 z(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Nl=class extends mc{constructor(e){super(2,e);Nl.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!ix(e.kernelSize,"number",1,2))throw new z(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Nl.className="Conv2D";Q.registerClass(Nl);var fc=class extends mc{constructor(e){super(3,e);fc.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 z(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};fc.className="Conv3D";Q.registerClass(fc);var fd=class extends Nl{constructor(e){super(e);if(this.inputSpec=[new St({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Je(e),e.length!==4)throw new z("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let o=e[t],n=this.kernelSize.concat([this.filters,o]);this.kernel=this.addWeight("kernel",n,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new St({ndim:4,axes:{[t]:o}})],this.built=!0}call(e,t){return V(()=>{let o=Fe(e);if(o.shape.length!==4)throw new z(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${o.shape.length}`);let n=o.shape,s=n[0],a,i;this.dataFormat==="channelsFirst"?(a=2,i=3):(a=1,i=2);let l=n[a],u=n[i],c=this.kernelSize[0],p=this.kernelSize[1],m=this.strides[0],f=this.strides[1],d=pd(l,m,c,this.padding),h=pd(u,f,p,this.padding),g=[s,d,h,this.filters];this.dataFormat!=="channelsLast"&&(o=Ue(o,[0,2,3,1]));let x=vu(o,this.kernel.read(),g,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(x=Ue(x,[0,3,1,2])),this.bias!=null&&(x=uo(x,this.bias.read(),this.dataFormat)),this.activation!=null&&(x=this.activation.apply(x)),x})}computeOutputShape(e){e=Je(e);let t=e.slice(),o,n,s;this.dataFormat==="channelsFirst"?(o=1,n=2,s=3):(o=3,n=1,s=2);let a=this.kernelSize[0],i=this.kernelSize[1],l=this.strides[0],u=this.strides[1];return t[o]=this.filters,t[n]=pd(t[n],l,a,this.padding),t[s]=pd(t[s],u,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};fd.className="Conv2DTranspose";Q.registerClass(fd);var YC=class extends mc{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 z("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new z("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 z(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=pt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=bt(t.depthwiseRegularizer),this.depthwiseConstraint=Ot(t.depthwiseConstraint),this.pointwiseInitializer=pt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=bt(t.pointwiseRegularizer),this.pointwiseConstraint=Ot(t.pointwiseConstraint)}build(e){if(e=Je(e),e.length<this.rank+2)throw new z(`Inputs to SeparableConv${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 z(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let o=e[t],n=this.kernelSize.concat([o,this.depthMultiplier]),s=[];for(let i=0;i<this.rank;++i)s.push(1);s.push(o*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",n,"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 St({ndim:this.rank+2,axes:{[t]:o}})],this.built=!0}call(e,t){return V(()=>{e=Fe(e);let o;if(this.rank===1)throw new Se("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=Ue(e,[0,2,3,1])),o=Um(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(o=uo(o,this.bias.read(),this.dataFormat)),this.activation!=null&&(o=this.activation.apply(o)),this.dataFormat==="channelsFirst"&&(o=Ue(o,[0,3,1,2])),o})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=_t(this.depthwiseInitializer),e.pointwiseInitializer=_t(this.pointwiseInitializer),e.depthwiseRegularizer=st(this.depthwiseRegularizer),e.pointwiseRegularizer=st(this.pointwiseRegularizer),e.depthwiseConstraint=Ft(this.depthwiseConstraint),e.pointwiseConstraint=Ft(this.pointwiseConstraint),e}};YC.className="SeparableConv";var dd=class extends YC{constructor(e){super(2,e)}};dd.className="SeparableConv2D";Q.registerClass(dd);var dc=class extends mc{constructor(e){super(1,e);dc.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"&&!ix(e.kernelSize,"number",1,1))throw new z(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};dc.className="Conv1D";Q.registerClass(dc);var hd=class extends Me{constructor(e){super(e);typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return V(()=>{if(e=Fe(e),this.dataFormat==="channelsLast"){let o=Vf(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Vf(o,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let o=Vf(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Vf(o,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};hd.className="Cropping2D";Q.registerClass(hd);var gd=class extends Me{constructor(e){super(e);this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,FM(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],o=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,o]}else{let t=e[1]==null?null:this.size[0]*e[1],o=e[2]==null?null:this.size[1]*e[2];return[e[0],t,o,e[3]]}}call(e,t){return V(()=>{let o=Fe(e),n=o.shape;if(this.dataFormat==="channelsFirst"){o=Ue(o,[0,2,3,1]);let s=this.size[0]*n[2],a=this.size[1]*n[3],i=this.interpolation==="nearest"?o.resizeNearestNeighbor([s,a]):o.resizeBilinear([s,a]);return Ue(i,[0,3,1,2])}else{let s=this.size[0]*n[1],a=this.size[1]*n[2];return this.interpolation==="nearest"?o.resizeNearestNeighbor([s,a]):o.resizeBilinear([s,a])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};gd.className="UpSampling2D";Q.registerClass(gd);function ZJ(r,e,t=[1,1],o="valid",n,s){return V(()=>{n==null&&(n=Zr()),$t(n);let a=md(r,n);if(r.rank!==4)throw new z(`Input for depthwiseConv2d is required to be 4-D, but is instead ${r.rank}-D`);if(e.rank!==4)throw new z(`depthwiseKernel is required to be 4-D, but is instead ${e.rank}-D`);return a=Is(a,e,t,o==="same"?"same":"valid","NHWC",s),n==="channelsFirst"&&(a=Ue(a,[0,3,1,2])),a})}var xd=class extends jp{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=pt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Ot(e.depthwiseConstraint),this.depthwiseRegularizer=bt(e.depthwiseRegularizer)}build(e){if(e=Je(e),e.length<4)throw new z(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new z(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let o=e[t],n=[this.kernelSize[0],this.kernelSize[1],o,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",n,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[o*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return V(()=>{e=Fe(e);let o=ZJ(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(o=uo(o,this.bias.read(),this.dataFormat)),this.activation!=null&&(o=this.activation.apply(o)),o})}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],o=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,s=fo(t,this.kernelSize[0],this.padding,this.strides[0]),a=fo(o,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],n,s,a]:[e[0],s,a,n]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=_t(this.depthwiseInitializer),e.depthwiseRegularizer=st(this.depthwiseRegularizer),e.depthwiseConstraint=Ft(this.depthwiseRegularizer),e}};xd.className="DepthwiseConv2D";Q.registerClass(xd);function ZC(r,e,t,o){if(Array.isArray(r)){if(e!=null||t!=null)throw new z("When inputs is an array, neither initialState or constants should be provided");o!=null&&(t=r.slice(r.length-o,r.length),r=r.slice(0,r.length-o)),r.length>1&&(e=r.slice(1,r.length)),r=r[0]}function n(s){return s==null||Array.isArray(s)?s:[s]}return e=n(e),t=n(t),{inputs:r,initialState:e,constants:t}}function JC(r,e,t,o=!1,n,s,a=!1,i=!1){return V(()=>{let l=e.shape.length;if(l<3)throw new z(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(zr(2,l));if(e=Ue(e,u),s!=null)throw new Se("The rnn() functoin of the deeplearn.js backend does not support constants yet.");a&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),n!=null&&(n=n.asType("bool").asType("float32"),n.rank===l-1&&(n=ar(n,-1)),n=Ue(n,u)),o&&(e=qt(e,0),n!=null&&(n=qt(n,0)));let c=[],p,m=t,f=e.shape[0],d=pr(e),h;n!=null&&(h=pr(n));for(let x=0;x<f;++x){let b=d[x],w=V(()=>r(b,m));if(n==null)p=w[0],m=w[1];else{let k=V(()=>{let _=h[x],D=tr(_).sub(_),T=w[0].mul(_).add(m[0].mul(D)),R=m.map((O,M)=>w[1][M].mul(_).add(O.mul(D)));return{output:T,newStates:R}});p=k.output,m=k.newStates}i&&c.push(p)}let g;return i&&(g=Bt(c,1)),[p,g,m]})}var ho=class extends Me{constructor(e){super(e);let t;if(e.cell==null)throw new z("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Up({cells:e.cell}):t=e.cell,t.stateSize==null)throw new z("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 St({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 zr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){hx(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let o=t[0],n;if(this.returnSequences?n=[e[0],e[1],o]:n=[e[0],o],this.returnState){let s=[];for(let a of t)s.push([e[0],a]);return[n].concat(s)}else return n}computeMask(e,t){return V(()=>{Array.isArray(t)&&(t=t[0]);let o=this.returnSequences?t:null;if(this.returnState){let n=this.states.map(s=>null);return[o].concat(n)}else return o})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let o=0;o<e;++o)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 Se("Constants support is not implemented in RNN yet.");hx(e)&&(e=e[0]),e=e;let o=this.stateful?e[0]:null,n=e.slice(2);this.inputSpec[0]=new St({shape:[o,null,...n]});let s=[e[0]].concat(e.slice(2));if(t!=null)throw new Se("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(!y.arraysEqual(this.stateSpec.map(i=>i.shape[i.shape.length-1]),a))throw new z(`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(i=>new St({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){V(()=>{if(!this.stateful)throw new So("Cannot call resetStates() on an RNN Layer that is not stateful.");let o=this.inputSpec[0].shape[0];if(o==null)throw new z("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(n=>ht([o,n])):this.states_=[ht([o,this.cell.stateSize])];else if(e==null)Ae(this.states_),this.keptStates!=null&&(Ae(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(n=>ht([o,n])):this.states_[0]=ht([o,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new z(`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()):Ae(this.states_);for(let n=0;n<this.states_.length;++n){let s=e[n],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[n]:this.cell.stateSize,i=[o,a];if(!y.arraysEqual(s.shape,i))throw new z(`State ${n} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${s.shape}`);this.states_[n]=s}}this.states_=this.states_.map(n=>Et(n.clone()))})}apply(e,t){let o=t==null?null:t.initialState,n=t==null?null:t.constants;t==null&&(t={});let s=ZC(e,o,n,this.numConstants);e=s.inputs,o=s.initialState,n=s.constants;let a=[],i=[];if(o!=null){t.initialState=o,a=a.concat(o),this.stateSpec=[];for(let u of o)this.stateSpec.push(new St({shape:u.shape}));i=i.concat(this.stateSpec)}if(n!=null&&(t.constants=n,a=a.concat(n),this.numConstants=n.length),a[0]instanceof Vr){let u=[e].concat(a),c=this.inputSpec.concat(i),p=this.inputSpec;this.inputSpec=c;let m=super.apply(u,t);return this.inputSpec=p,m}else return super.apply(e,t)}call(e,t){return V(()=>{let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;e=Fe(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 z(`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 i={training:n},u=JC((d,h)=>{let g=this.cell.call([d].concat(h),i);return[g[0],g.slice(1)]},e,s,this.goBackwards,o,null,this.unroll,this.returnSequences),c=u[0],p=u[1],m=u[2];this.stateful&&this.resetStates(m,n);let f=this.returnSequences?p:c;return this.returnState?[f].concat(m):f})}getInitialState(e){return V(()=>{let t=ht(e.shape);return t=ge(t,[1,2]),t=Va(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(o=>o>1?cx(t,[1,o]):t):this.cell.stateSize>1?[cx(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 o=this.cell.getConfig();return this.getClassName()===ho.className&&(t.cell={className:this.cell.getClassName(),config:o}),Object.assign({},o,e,t)}static fromConfig(e,t,o={}){let n=t.cell,s=Qr(n,o);return new e(Object.assign(t,{cell:s}))}};ho.className="RNN";Q.registerClass(ho);var Sl=class extends Me{},Hp=class extends Sl{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,Ut(this.units,"units"),this.activation=Vs(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=bt(e.kernelRegularizer),this.recurrentRegularizer=bt(e.recurrentRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.kernelConstraint=Ot(e.kernelConstraint),this.recurrentConstraint=Ot(e.recurrentConstraint),this.biasConstraint=Ot(e.biasConstraint),this.dropout=sc([1,Ls([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=sc([1,Ls([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(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 V(()=>{if(e=e,e.length!==2)throw new z(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let o=e[1];e=e[0];let n=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Wa({ones:()=>tr(e),rate:this.dropout,training:n})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Wa({ones:()=>tr(o),rate:this.recurrentDropout,training:n}));let s,a=this.dropoutMask,i=this.recurrentDropoutMask;a!=null?s=rs(P(e,a),this.kernel.read()):s=rs(e,this.kernel.read()),this.bias!=null&&(s=uo(s,this.bias.read())),i!=null&&(o=P(o,i));let l=ee(s,rs(o,this.recurrentKernel.read()));return this.activation!=null&&(l=this.activation.apply(l)),[l,l]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Bs(this.activation),useBias:this.useBias,kernelInitializer:_t(this.kernelInitializer),recurrentInitializer:_t(this.recurrentInitializer),biasInitializer:_t(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),recurrentConstraint:Ft(this.recurrentConstraint),biasConstraint:Ft(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};Hp.className="SimpleRNNCell";Q.registerClass(Hp);var yd=class extends ho{constructor(e){e.cell=new Hp(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}static fromConfig(e,t){return new e(t)}};yd.className="SimpleRNN";Q.registerClass(yd);var qp=class extends Sl{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 z("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Ut(this.units,"units"),this.activation=Vs(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Vs(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=bt(e.kernelRegularizer),this.recurrentRegularizer=bt(e.recurrentRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.kernelConstraint=Ot(e.kernelConstraint),this.recurrentConstraint=Ot(e.recurrentConstraint),this.biasConstraint=Ot(e.biasConstraint),this.dropout=sc([1,Ls([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=sc([1,Ls([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(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 V(()=>{if(e=e,e.length!==2)throw new z(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let o=t.training==null?!1:t.training,n=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Wa({ones:()=>tr(e),rate:this.dropout,training:o,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Wa({ones:()=>tr(n),rate:this.recurrentDropout,training:o,count:3}));let s=this.dropoutMask,a=this.recurrentDropoutMask,i,l,u;0<this.dropout&&this.dropout<1&&(e=P(e,s[0]));let c=rs(e,this.kernel.read());this.useBias&&(c=uo(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(n=P(n,a[0]));let p=this.recurrentKernel.read(),[m,f]=cr(p,[2*this.units,this.units],p.rank-1),d=rs(n,m),[h,g,x]=cr(c,3,c.rank-1),[b,w]=cr(d,2,d.rank-1);i=this.recurrentActivation.apply(ee(h,b)),l=this.recurrentActivation.apply(ee(g,w));let k=rs(P(l,n),f);u=this.activation.apply(ee(x,k));let _=ee(P(i,n),P(ee(1,He(i)),u));return[_,_]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Bs(this.activation),recurrentActivation:Bs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:_t(this.kernelInitializer),recurrentInitializer:_t(this.recurrentInitializer),biasInitializer:_t(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),recurrentConstraint:Ft(this.recurrentConstraint),biasConstraint:Ft(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};qp.className="GRUCell";Q.registerClass(qp);var bd=class extends ho{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new qp(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};bd.className="GRU";Q.registerClass(bd);var Tl=class extends Sl{constructor(e){super(e);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Ut(this.units,"units"),this.activation=Vs(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Vs(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=pt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=bt(e.kernelRegularizer),this.recurrentRegularizer=bt(e.recurrentRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.kernelConstraint=Ot(e.kernelConstraint),this.recurrentConstraint=Ot(e.recurrentConstraint),this.biasConstraint=Ot(e.biasConstraint),this.dropout=sc([1,Ls([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=sc([1,Ls([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=Je(e);let o=e[e.length-1];this.kernel=this.addWeight("kernel",[o,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let n;if(this.useBias){if(this.unitForgetBias){let s=this.biasInitializer,a=this.units;n=new(t=class extends co{apply(l,u){let c=s.apply([a]),p=new ac().apply([a]),m=s.apply([a*2]);return _C(_C(c,p),m)}},t.className="CustomInit",t)}else n=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,n,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return V(()=>{let o=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new z(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=e[1],s=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Wa({ones:()=>tr(e),rate:this.dropout,training:o,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Wa({ones:()=>tr(n),rate:this.recurrentDropout,training:o,count:4}));let a=this.dropoutMask,i=this.recurrentDropoutMask,l,u,c,p;0<this.dropout&&this.dropout<1&&(e=P(e,a[0]));let m=rs(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(n=P(n,i[0])),m=ee(m,rs(n,this.recurrentKernel.read())),this.useBias&&(m=uo(m,this.bias.read()));let[f,d,h,g]=cr(m,4,m.rank-1);l=this.recurrentActivation.apply(f),u=this.recurrentActivation.apply(d),c=ee(P(u,s),P(l,this.activation.apply(h))),p=this.recurrentActivation.apply(g);let x=P(p,this.activation.apply(c));return[x,x,c]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Bs(this.activation),recurrentActivation:Bs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:_t(this.kernelInitializer),recurrentInitializer:_t(this.recurrentInitializer),biasInitializer:_t(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:st(this.kernelRegularizer),recurrentRegularizer:st(this.recurrentRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),recurrentConstraint:Ft(this.recurrentConstraint),biasConstraint:Ft(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Tl.className="LSTMCell";Q.registerClass(Tl);var wd=class extends ho{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Tl(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};wd.className="LSTM";Q.registerClass(wd);var Up=class extends Sl{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return V(()=>{e=e;let o=e.slice(1),n=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?n.push(o.splice(0,i.stateSize.length)):n.push(o.splice(0,1));n.reverse();let s=[],a;for(let i=0;i<this.cells.length;++i){let l=this.cells[i];o=n[i],i===0?a=[e[0]].concat(o):a=[a[0]].concat(o),a=l.call(a,t),s.push(a.slice(1))}o=[];for(let i of s.slice().reverse())o.push(...i);return[a[0]].concat(o)})}build(e){hx(e)&&(e=e[0]),e=e;let t;this.cells.forEach((o,n)=>{Ms(`RNNCell_${n}`,()=>{o.build(e),Array.isArray(o.stateSize)?t=o.stateSize[0]:t=o.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=s=>({className:s.getClassName(),config:s.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,o={}){let n=[];for(let s of t.cells)n.push(Qr(s,o));return new e({cells:n})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let o of this.cells)t.push(...o.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return Yf(e)}setWeights(e){let t=[];for(let o of this.cells){let n=o.weights.length,s=e.splice(n);for(let a=0;a<o.weights.length;++a)t.push([o.weights[a],s[a]])}Lp(t)}};Up.className="StackedRNNCells";Q.registerClass(Up);function Wa(r){let{ones:e,rate:t,training:o=!1,count:n=1}=r,s=()=>mx(e(),t),a=()=>bl(s,e,o);return!n||n<=1?Et(a().clone()):Array(n).fill(void 0).map(a).map(l=>Et(l.clone()))}var JJ=function(r,e){var t={};for(var o in r)Object.prototype.hasOwnProperty.call(r,o)&&e.indexOf(o)<0&&(t[o]=r[o]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var n=0,o=Object.getOwnPropertySymbols(r);n<o.length;n++)e.indexOf(o[n])<0&&Object.prototype.propertyIsEnumerable.call(r,o[n])&&(t[o[n]]=r[o[n]]);return t};var QC=class extends ho{constructor(e){if(e.unroll)throw new Se("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Se("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new St({ndim:5})]}call(e,t){return V(()=>{if(this.cell.dropoutMask!=null&&(Ae(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Ae(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new z("ConvRNN2D cell does not support constants");let o=t==null?null:t.mask,n=t==null?null:t.training,s=t==null?null:t.initialState;return super.call(e,{mask:o,training:n,initialState:s})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return V(()=>{let{stateSize:t}=this.cell,o=e.shape,n=this.computeSingleOutputShape(o),s=[n[0],...n.slice(2)],a=ht(s);return Array.isArray(t)?Array(t.length).fill(a):[a]})}resetStates(e,t=!1){V(()=>{if(!this.stateful)throw new So("Cannot call resetStates() on an RNN Layer that is not stateful.");let o=this.inputSpec[0].shape,n=this.computeSingleOutputShape(o),s=[n[0],...n.slice(2)];if(o[0]==null)throw new z("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>ht(s)):this.states_=[ht(s)];else if(e==null)Ae(this.states_),this.keptStates!=null&&(Ae(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>ht(s)):this.states_[0]=ht(s);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new z(`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()):Ae(this.states_);for(let i=0;i<this.states_.length;++i){let l=e[i],u=s;if(!y.arraysEqual(l.shape,u))throw new z(`State ${i} is incompatible with layer ${this.name}: expected shape=${u}, received shape=${l.shape}`);this.states_[i]=l}}this.states_=this.states_.map(i=>Et(i.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:o,kernelSize:n,padding:s,strides:a,dilationRate:i}=this.cell,l=t==="channelsFirst",u=e[l?3:2],c=e[l?4:3],p=fo(u,n[0],s,a[0],i[0]),m=fo(c,n[1],s,a[1],i[1]);return[...e.slice(0,2),...l?[o,p,m]:[p,m,o]]}};QC.className="ConvRNN2D";var Kp=class extends Tl{constructor(e){let{filters:t,kernelSize:o,strides:n,padding:s,dataFormat:a,dilationRate:i}=e;super(Object.assign({},e,{units:t}));this.filters=t,Ut(this.filters,"filters"),this.kernelSize=Il(o,2,"kernelSize"),this.kernelSize.forEach(l=>Ut(l,"kernelSize")),this.strides=Il(n||1,2,"strides"),this.strides.forEach(l=>Ut(l,"strides")),this.padding=s||"valid",Jr(this.padding),this.dataFormat=a||"channelsLast",$t(this.dataFormat),this.dilationRate=Il(i||1,2,"dilationRate"),this.dilationRate.forEach(l=>Ut(l,"dilationRate"))}build(e){var t;e=Je(e);let o=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[o]==null)throw new z(`The channel dimension of the input should be defined. Found ${e[o]}`);let n=e[o],s=4,a=this.kernelSize.concat([n,this.filters*s]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*s]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let l;if(this.unitForgetBias){let u=this.biasInitializer,c=this.filters;l=new(t=class extends co{apply(m,f){let d=u.apply([c]),h=Nr([c]),g=u.apply([c*2]);return Tp([d,h,g])}},t.className="CustomInit",t)}else l=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*s],null,l,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return V(()=>{if(e.length!==3)throw new z(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let o=t.training||!1,n=e[0],s=e[1],a=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=Wa({ones:()=>tr(n),rate:this.dropout,training:o,count:i}));let l=this.dropoutMask,u=(J,ie,ue)=>!ie||!ie[ue]?J:P(ie[ue],J),c=u(n,l,0),p=u(n,l,1),m=u(n,l,2),f=u(n,l,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=Wa({ones:()=>tr(s),rate:this.recurrentDropout,training:o,count:i}));let d=this.recurrentDropoutMask,h=u(s,d,0),g=u(s,d,1),x=u(s,d,2),b=u(s,d,3),w=3,[k,_,D,T]=cr(this.kernel.read(),i,w),[R,O,M,G]=this.useBias?cr(this.bias.read(),i):[null,null,null,null];c=this.inputConv(c,k,R,this.padding),p=this.inputConv(p,_,O,this.padding),m=this.inputConv(m,D,M,this.padding),f=this.inputConv(f,T,G,this.padding);let[j,U,H,q]=cr(this.recurrentKernel.read(),i,w);h=this.recurrentConv(h,j),g=this.recurrentConv(g,U),x=this.recurrentConv(x,H),b=this.recurrentConv(b,q);let X=this.recurrentActivation.apply(ee(c,h)),oe=this.recurrentActivation.apply(ee(p,g)),Y=ee(P(oe,a),P(X,this.activation.apply(ee(m,x)))),re=P(this.recurrentActivation.apply(ee(f,b)),this.activation.apply(Y));return[re,re,Y]})}getConfig(){let e=super.getConfig(),{units:t}=e,o=JJ(e,["units"]),n={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},o,n)}inputConv(e,t,o,n){let s=Kr(e,t,this.strides,n||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return o?uo(s,o,this.dataFormat):s}recurrentConv(e,t){return Kr(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Kp.className="ConvLSTM2DCell";Q.registerClass(Kp);var kd=class extends QC{constructor(e){let t=new Kp(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};kd.className="ConvLSTM2D";Q.registerClass(kd);var Xp=class extends Me{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,o=[];for(let n=0;n<this.noiseShape.length;++n)o.push(this.noiseShape[n]==null?t[n]:this.noiseShape[n]);return o}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);if(0<this.rate&&this.rate<1){let n=t.training==null?!1:t.training,s=this.getNoiseShape(o);return bl(()=>mx(o,this.rate,s,this.seed),()=>o,n)}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()}};Xp.className="Dropout";Q.registerClass(Xp);var _d=class extends Xp{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};_d.className="SpatialDropout1D";Q.registerClass(_d);var vd=class extends Me{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,Ut(this.units,"units"),this.activation=Vs(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=pt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=pt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Ot(e.kernelConstraint),this.biasConstraint=Ot(e.biasConstraint),this.kernelRegularizer=bt(e.kernelRegularizer),this.biasRegularizer=bt(e.biasRegularizer),this.activityRegularizer=bt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=Je(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=Je(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e),n=ax(this.activation.getClassName()),s;return n!=null?s=rs(o,this.kernel.read(),n,this.bias?this.bias.read():null):(s=rs(o,this.kernel.read()),this.bias!=null&&(s=uo(s,this.bias.read())),this.activation!=null&&(s=this.activation.apply(s))),s})}getConfig(){let e={units:this.units,activation:Bs(this.activation),useBias:this.useBias,kernelInitializer:_t(this.kernelInitializer),biasInitializer:_t(this.biasInitializer),kernelRegularizer:st(this.kernelRegularizer),biasRegularizer:st(this.biasRegularizer),activityRegularizer:st(this.activityRegularizer),kernelConstraint:Ft(this.kernelConstraint),biasConstraint:Ft(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};vd.className="Dense";Q.registerClass(vd);var Cd=class extends Me{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=Je(e);for(let t of e.slice(1))if(t==null)throw new z(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],ts(e,1)]}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);if(this.dataFormat==="channelsFirst"&&o.rank>1){let n=[0];for(let s=2;s<o.rank;++s)n.push(s);n.push(1),o=o.transpose(n)}return VM(o)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};Cd.className="Flatten";Q.registerClass(Cd);var Id=class extends Me{constructor(e){super(e);this.supportsMasking=!0,this.activation=Vs(e.activation)}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return this.activation.apply(o)})}getConfig(){let e={activation:Bs(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Id.className="Activation";Q.registerClass(Id);var Nd=class extends Me{constructor(e){super(e);this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return V(()=>(e=Fe(e),zM(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};Nd.className="RepeatVector";Q.registerClass(Nd);var Sd=class extends Me{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 o="Total size of new array must be unchanged.",n=t.slice(),s=1,a=null;for(let l=0;l<n.length;++l){let u=n[l];if(this.isUnknown(u))if(a===null)a=l;else throw new z("Can only specifiy one unknown dimension.");else s*=u}let i=ts(e);if(a!==null){if(s===0||i%s!=0)throw new z(o);n[a]=i/s}else if(i!==s)throw new z(o);return n}computeOutputShape(e){let t=!1;for(let o=0;o<e.length;++o)if(this.isUnknown(e[o])){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 V(()=>{this.invokeCallHook(e,t);let o=Fe(e),n=o.shape,s=n.slice(0,1).concat(this.fixUnknownDimension(n.slice(1),this.targetShape));return o.reshape(s)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Sd.className="Reshape";Q.registerClass(Sd);var Td=class extends Me{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=zr(1,e.dims.length+1);if(!y.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 St({ndim:this.dims.length+1})]}computeOutputShape(e){e=Je(e);let t=e.slice();return this.dims.forEach((o,n)=>{t[n+1]=e[o]}),t}call(e,t){return Ue(Fe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Td.className="Permute";Q.registerClass(Td);var Ad=class extends Me{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let o=Fe(e),n=-1;return sl(Vn(o,this.maskValue),n)}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e),n=-1,s=!0,a=sl(Vn(o,this.maskValue),n,s);return o.mul(a.asType(o.dtype))})}};Ad.className="Masking";Q.registerClass(Ad);var Ed=class extends Me{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(yt(e.inputLength))}this.inputDim=e.inputDim,Ut(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Ut(this.outputDim,"outputDim"),this.embeddingsInitializer=pt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=bt(e.embeddingsRegularizer),this.activityRegularizer=bt(e.activityRegularizer),this.embeddingsConstraint=Ot(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return V(()=>this.maskZero?(e=Fe(e),Vn(e,Ce(e))):null)}computeOutputShape(e){if(e=Je(e),this.inputLength==null)return[...e,this.outputDim];let t=yt(this.inputLength);if(t.length!==e.length-1)throw new z(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let o=0;for(let n=0;n<t.length;++n){let s=t[n],a=e[n+1];if(s!=null&&a!=null&&s!==a)throw new z(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);s==null&&(t[o]=a),o++}}return[e[0],...t,this.outputDim]}call(e,t){return V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return o.dtype!=="int32"&&(o=Ba(o,"int32")),px(this.embeddings.read(),o.as1D()).reshape(Je(this.computeOutputShape(o.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:_t(this.embeddingsInitializer),embeddingsRegularizer:st(this.embeddingsRegularizer),activityRegularizer:st(this.activityRegularizer),embeddingsConstraint:Ft(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Ed.className="Embedding";Q.registerClass(Ed);var Al=class extends Me{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new Se}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let o=e.slice(0,e.length-t.length);for(let n=0;n<t.length;++n){let s=e[e.length-t.length+n],a=t[n];if(s==null||a==null||s<0||a<0)o.push(null);else if(s===1)o.push(a);else if(a===1)o.push(s);else{if(s!==a)throw new z("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));o.push(s)}}return o}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[Je(e)]),e=e,e.length<2)throw new z(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let s of e)s!=null&&s[0]!==null&&t.push(s[0]);if(t=es(t),t.length>1)throw new z(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let o=e[0]==null?null:e[0].slice(1);for(let s=1;s<e.length;++s){let a=e[s]==null?null:e[s].slice(1);o=this.computeElementwiseOpOutputShape(o,a)}let n=e.map(s=>s.length);e.indexOf(null)===-1&&es(n).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return V(()=>{if(e=e,this.reshapeRequired){let o=[],n=e.map(s=>s.rank);if(n.indexOf(null)===-1){let s=Ls(n);for(let a of e){let i=a.rank;for(let l=0;l<s-i;++l)a=Va(a,1);o.push(a)}return this.mergeFunction(o)}else{let s=!1;for(let l of e){let u=l.rank;if(u==null){let c=l.shape,p=c[0],m=c.slice(1).concat([p]),f=l.reshape([p].concat(ts(c.slice(1))));f=Ue(f,[1,0]),f=f.reshape(m),o.push(f),s=!0}else if(u>1){let c=zr(1,u).concat([0]);o.push(Ue(l,c)),s=!0}else o.push(l)}let a=this.mergeFunction(o),i=a.rank;if(s){if(i==null){let l=a.shape,u=l.length,c=l[u-1],p=[c].concat(l.slice(0,l.length-1));a=Ue(a.reshape([-1,c]),[1,0]).reshape(p)}else if(i>1){let l=[i-1].concat(zr(0,i-1));a=Ue(a,l)}}return a}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let n=1;n<e.length;++n){let s=e[n]==null?null:e[n].slice(1);t=this.computeElementwiseOpOutputShape(t,s)}let o=[];for(let n of e)n!=null&&n[0]!==null&&o.push(n[0]);return o=es(o),o.length===1?t=o.concat(t):t=[null].concat(t),t}computeMask(e,t){return V(()=>{if(t==null)return null;if(!Array.isArray(t))throw new z("`mask` should be an Array");if(!Array.isArray(e))throw new z("`inputs` should be an Array");if(t.length!==e.length)throw new z(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(n=>n==null))return null;t=t.map(n=>n==null?n:ar(n,0));let o=t[0];for(let n=1;n<t.length-1;++n)o=hr(o,t[n]);return o})}},Dd=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0].clone();for(let o=1;o<e.length;++o)t=ee(t,e[o]);return t})}};Dd.className="Add";Q.registerClass(Dd);var $d=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0].clone();for(let o=1;o<e.length;++o)t=P(t,e[o]);return t})}};$d.className="Multiply";Q.registerClass($d);var Rd=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0].clone();for(let o=1;o<e.length;++o)t=ee(t,e[o]);return P(1/e.length,t)})}};Rd.className="Average";Q.registerClass(Rd);var Fd=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0];for(let o=1;o<e.length;++o)t=Yr(t,e[o]);return t})}};Fd.className="Maximum";Q.registerClass(Fd);var Od=class extends Al{constructor(e){super(e)}mergeFunction(e){return V(()=>{let t=e[0];for(let o=1;o<e.length;++o)t=As(t,e[o]);return t})}};Od.className="Minimum";Q.registerClass(Od);var Pd=class extends Al{constructor(e){super(e);this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new z("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let n of e)if(n!=null){t=!1;break}if(t)return;let o=[];for(let n=0;n<e.length;++n){let s=e[n].slice();s.splice(this.axis,1);let a=!1;for(let i of o)if(y.arraysEqual(i,s)){a=!0;break}a||o.push(s)}if(o.length>1)throw new z("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return V(()=>Tp(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new z("A `Concatenate` layer should be called on a list of inputs.");let t=e,o=t[0].slice(),n=this.axis<0?o.length+this.axis:this.axis;for(let s of t.slice(1)){if(o[n]==null||s[n]==null){o[n]=null;break}o[n]+=s[n]}return o}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new z("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new z("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new z(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return V(()=>{let o=!0;if(t.forEach(a=>{if(a!=null){o=!1;return}}),o)return null;let n=[];for(let a=0;a<e.length;++a)t[a]==null?n.push(tr(e[a]).asType("bool")):t[a].rank<e[a].rank?n.push(ar(t[a],-1)):n.push(t[a]);let s=Ze(n,this.axis);return bu(s,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Pd.className="Concatenate";Q.registerClass(Pd);function Md(r,e){for(;r<0;)r+=e;return r}function QJ(r,e,t){if(r.shape.length>3||e.shape.length>3)throw new Se("batchDot is not implemented for tensors of 4D or higher rank yet");if(y.assert(r.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${r.shape.length}`),y.assert(r.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${e.shape.length}`),typeof t=="number"&&(t=[t,t]),r.dtype==="complex64"||e.dtype==="complex64")throw new Se("batchDot is not implemented for complex64-type Tensors yet.");let o=r.shape.length,n=e.shape.length;t==null&&(t=[o-1,n-2]);let s=t;return V(()=>{let a;if(o>n){a=o-n;let l=[];for(let u=0;u<a;++u)l.push(1);e=e.reshape(e.shape.concat(l))}else if(n>o){a=n-o;let l=[];for(let u=0;u<a;++u)l.push(1);r=r.reshape(r.shape.concat(l))}else a=0;let i;if(r.shape.length===2&&e.shape.length===2)s[0]===s[1]?i=r.mul(e).sum(s[0]):i=r.transpose([1,0]).mul(e).sum(s[1]);else{let l=s[0]!==r.shape.length-1,u=s[1]===e.shape.length-1;i=r.matMul(e,l,u)}if(a>0){let l;o>n?l=o+n-3:l=o-1;let u=[];for(let c=l;c<l+a;++c)u.push(c);i=i.squeeze(u)}return i.shape.length===1&&(i=i.expandDims(1)),i})}var Ld=class extends Al{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){y.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],o=e[1];if(t.length>3||o.length>3)throw new Se("Dot layer does not support tensors of 4D or higher rank yet.");let n=this.interpretAxes(t,o);if(t[n[0]]!==o[n[1]])throw new z(`Dimension incompatibility: ${t[n[0]]} !== ${o[n[1]]}`)}mergeFunction(e){if(e.length!==2)throw new z(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],o=e[1],n;return Array.isArray(this.axes)?n=this.axes.map((s,a)=>Md(s,e[a].shape.length)):n=[Md(this.axes,t.shape.length),Md(this.axes,o.shape.length)],this.normalize&&(t=Zf(t,n[0]),o=Zf(o,n[1])),QJ(t,o,n)}interpretAxes(e,t){let o;return Array.isArray(this.axes)?o=this.axes:o=[Md(this.axes,e.length),Md(this.axes,t.length)],o}computeOutputShape(e){y.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),o=e[1].slice();if(t.length>3||o.length>3)throw new Se("Dot layer does not support tensors of 4D or higher rank yet.");let n=this.interpretAxes(t,o);t.splice(n[0],1),o.splice(n[1],1),o.splice(0,1);let s=t.concat(o);return s.length===1&&s.push(1),s}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};Ld.className="Dot";Q.registerClass(Ld);var zd=class extends Me{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 V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return bl(()=>Ap(o.shape,0,this.stddev).add(o),()=>o,t.training||!1)})}};zd.className="GaussianNoise";Q.registerClass(zd);var Bd=class extends Me{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 V(()=>{this.invokeCallHook(e,t);let o=Fe(e);return this.rate>0&&this.rate<1?bl(()=>{let s=Math.sqrt(this.rate/(1-this.rate));return o.mul(Ap(o.shape,1,s))},()=>o,t.training||!1):o})}};Bd.className="GaussianDropout";Q.registerClass(Bd);var Vd=class extends Me{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Fe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return V(()=>{if(this.rate<1&&this.rate>0){let o=this._getNoiseShape(e);return bl(()=>{let s=Fe(e),a=1.6732632423543772,i=1.0507009873554805,l=-a*i,u=io(Es(o),this.rate);u=Ba(u,"float32");let c=((1-this.rate)*(1+this.rate*l**2))**-.5,p=-c*l*this.rate;return s.mul(u).add(u.add(-1).mul(l)).mul(c).add(p)},()=>Fe(e),t.training||!1)}return e})}};Vd.className="AlphaDropout";Q.registerClass(Vd);function Gd(r,e,t,o,n,s=.001){let a;if(r.rank===2)a=xw(r,e,t,o,n,s);else if(r.rank===3)a=yw(r,e,t,o,n,s);else if(r.rank===4)a=bw(r,e,t,o,n,s);else throw new Se(`batchNormalization is not implemented for array of rank ${r.rank} yet`);return a}function eQ(r,e,t,o,n=.001){return V(()=>{let s=Yc(r,o),a=s.mean,i=s.variance;return[Gd(r,a,i,t,e,n),a,i]})}function tQ(r,e,t,o,n=.001){return V(()=>{let s=Yc(r,o),a=s.mean,i=s.variance,l=[];for(let d of zr(0,r.rank))o.indexOf(d)!==-1?l.push(1):l.push(r.shape[d]);let u=a.reshape(l),c=i.reshape(l),p=e==null?null:e.reshape(l),m=t==null?null:t.reshape(l);return[Gd(r,u,c,m,p,n),a,i]})}function rQ(r,e,t,o,n=.001){return y.arraysEqual(o.slice().sort(),zr(0,r.rank-1))?eQ(r,e,t,o,n):tQ(r,e,t,o,n)}var Wd=class extends Me{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=pt(e.betaInitializer||"zeros"),this.gammaInitializer=pt(e.gammaInitializer||"ones"),this.movingMeanInitializer=pt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=pt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Ot(e.betaConstraint),this.gammaConstraint=Ot(e.gammaConstraint),this.betaRegularizer=bt(e.betaRegularizer),this.gammaRegularizer=bt(e.gammaRegularizer)}build(e){e=Je(e);let t=this.axis>=0?this.axis:this.axis+e.length,o=e[t];if(o==null)throw new z(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new St({ndim:e.length,axes:{[t]:o}})];let n=[o];this.scale&&(this.gamma=this.addWeight("gamma",n,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",n,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",n,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",n,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return V(()=>{let o=t.training==null?!1:t.training,n=Fe(e),s=n.shape,a=s.length,i=zr(0,a),l=this.axis>=0?this.axis:this.axis+a;i.splice(l,1);let u=Zn(1,a);u[l]=s[l];let c=i.slice();c.sort();let p=!y.arraysEqual(c,zr(0,a).slice(0,a-1)),m=()=>{if(p){let b=this.movingMean.read().reshape(u),w=this.movingVariance.read().reshape(u),k=this.center?this.beta.read().reshape(u):null,_=this.scale?this.gamma.read().reshape(u):null;return Gd(n,b,w,k,_,this.epsilon)}else return Gd(n,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!o)return m();let[f,d,h]=rQ(n,this.gamma.read(),this.beta.read(),i,this.epsilon),g=(b,w,k)=>{V(()=>{let _=1-k,D=b.read(),T=D.sub(w).mul(_);b.write(D.sub(T))})};return(()=>{g(this.movingMean,d,this.momentum),g(this.movingVariance,h,this.momentum)})(),f})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:_t(this.betaInitializer),gammaInitializer:_t(this.gammaInitializer),movingMeanInitializer:_t(this.movingMeanInitializer),movingVarianceInitializer:_t(this.movingVarianceInitializer),betaRegularizer:st(this.betaRegularizer),gammaRegularizer:st(this.gammaRegularizer),betaConstraint:Ft(this.betaConstraint),gammaConstraint:Ft(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Wd.className="BatchNormalization";Q.registerClass(Wd);var jd=class extends Me{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=pt(e.betaInitializer||"zeros"),this.gammaInitializer=pt(e.gammaInitializer||"ones"),this.betaRegularizer=bt(e.betaRegularizer),this.gammaRegularizer=bt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=Je(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let s=0;s<this.axis.length;++s)this.axis[s]<0&&(this.axis[s]+=t);for(let s of this.axis)if(s<0||s>=t)throw new Error(`Invalid axis: ${s}`);if(this.axis.length!==es(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let o=this.axis.map(s=>e[s]),n=!0;this.scale?this.gamma=this.addWeight("gamma",o,"float32",this.gammaInitializer,this.gammaRegularizer,n):this.gamma=null,this.center?this.beta=this.addWeight("beta",o,"float32",this.betaInitializer,this.betaRegularizer,n):this.beta=null,this.built=!0}call(e,t){let o=Fe(e),n=o.shape,s=n.length;return V(()=>{let a=!0,{mean:i,variance:l}=Yc(o,this.axis,a),u=Zn(1,s);for(let h of this.axis)u[h]=n[h];let c=h=>h!=null&&h.shape.length!==s&&this.axis!==[s-1]?h.reshape(u):h,p=c(this.gamma.read()),m=c(this.beta.read()),f=[],d=[];for(let h=0;h<s;++h)this.axis.indexOf(h)!==-1?(f.push(n[h]),d.push(1)):(f.push(1),d.push(n[h]));return i=i.tile(f),l=l.tile(f),p=p.tile(d),m=m.tile(d),Gd(o,i,l,m,p,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:_t(this.betaInitializer),gammaInitializer:_t(this.gammaInitializer),betaRegularizer:st(this.betaRegularizer),gammaRegularizer:st(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};jd.className="LayerNormalization";Q.registerClass(jd);function oQ(r,e,t){return V(()=>{if(r.rank!==4)throw new z(`temporalPadding expects input tensor to be 4-D, but received a ${r.rank}-D tensor.`);if(e==null&&(e=[[1,1],[1,1]]),e.length!==2||e[0].length!==2||e[1].length!==2)throw new z("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(t==null&&(t=Zr()),t!=="channelsLast"&&t!=="channelsFirst")throw new z(`Unknown data format: ${t}. 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s==="max"?a=Na(r,e,t,i):a=wa(r,e,t,i),n==="channelsFirst"&&(a=Ue(a,[0,3,1,2])),a})}function TL(r,e,t,o,n,s){return V(()=>{$t(n),wC(s),Jr(o),t==null&&(t=[1,1,1]),o==null&&(o="valid"),n==null&&(n=Zr()),s==null&&(s="max"),r=XC(r,n);let a,i=o==="same"?"same":"valid";return s==="max"?a=Bm(r,e,t,i):a=Am(r,e,t,i),n==="channelsFirst"&&(a=Ue(a,[0,4,1,2,3])),a})}var e0=class extends Me{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new z(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Ut(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof 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$t(s),Jr(n),Ox(e,t,o,n,s,"avg")}};qd.className="AveragePooling1D";Q.registerClass(qd);var t0=class extends Me{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new z(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Ut(this.poolSize,"poolSize"),Ut(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),Jr(this.padding),this.inputSpec=[new St({ndim:4})]}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],o=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=fo(t,this.poolSize[0],this.padding,this.strides[0]),o=fo(o,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,o]:[e[0],t,o,e[3]]}call(e,t){return V(()=>(this.invokeCallHook(e,t),this.poolingFunction(Fe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Kd=class extends t0{constructor(e){super(e)}poolingFunction(e,t,o,n,s){return $t(s),Jr(n),Ox(e,t,o,n,s,"max")}};Kd.className="MaxPooling2D";Q.registerClass(Kd);var Xd=class extends t0{constructor(e){super(e)}poolingFunction(e,t,o,n,s){return $t(s),Jr(n),Ox(e,t,o,n,s,"avg")}};Xd.className="AveragePooling2D";Q.registerClass(Xd);var r0=class extends Me{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new z(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Ut(this.poolSize,"poolSize"),Ut(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),Jr(this.padding),this.inputSpec=[new St({ndim:5})]}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],o=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=fo(t,this.poolSize[0],this.padding,this.strides[0]),o=fo(o,this.poolSize[1],this.padding,this.strides[1]),n=fo(n,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,o,n]:[e[0],t,o,n,e[4]]}call(e,t){return V(()=>(this.invokeCallHook(e,t),this.poolingFunction(Fe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},Yd=class extends r0{constructor(e){super(e)}poolingFunction(e,t,o,n,s){return $t(s),Jr(n),TL(e,t,o,n,s,"max")}};Yd.className="MaxPooling3D";Q.registerClass(Yd);var Zd=class extends r0{constructor(e){super(e)}poolingFunction(e,t,o,n,s){return $t(s),Jr(n),TL(e,t,o,n,s,"avg")}};Zd.className="AveragePooling3D";Q.registerClass(Zd);var o0=class extends Me{constructor(e){super(e);this.inputSpec=[new St({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Se}},Jd=class extends o0{constructor(e){super(e||{})}call(e,t){return V(()=>{let o=Fe(e);return dt(o,1)})}};Jd.className="GlobalAveragePooling1D";Q.registerClass(Jd);var Qd=class extends o0{constructor(e){super(e||{})}call(e,t){return V(()=>{let o=Fe(e);return ur(o,1)})}};Qd.className="GlobalMaxPooling1D";Q.registerClass(Qd);var n0=class extends Me{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),this.inputSpec=[new St({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Se}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},eh=class extends n0{call(e,t){return V(()=>{let o=Fe(e);return this.dataFormat==="channelsLast"?dt(o,[1,2]):dt(o,[2,3])})}};eh.className="GlobalAveragePooling2D";Q.registerClass(eh);var th=class extends n0{call(e,t){return V(()=>{let o=Fe(e);return 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e(a)}},rh=class extends s0{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=Je(e),e.length<3)throw new z(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=Je(e);let t=[e[0]].concat(e.slice(2)),o=this.layer.computeOutputShape(t),n=e[1];return[o[0],n].concat(o.slice(1))}call(e,t){return V(()=>(e=Fe(e),JC((a,i)=>[Fe(this.layer.call(a,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};rh.className="TimeDistributed";Q.registerClass(rh);function nQ(r){Wi(RM,"BidirectionalMergeMode",r)}var sQ="concat",oh=class extends s0{constructor(e){super(e);let t=e.layer.getConfig(),o={};o.className=e.layer.getClassName(),o.config=t,this.forwardLayer=Qr(o),t.goBackwards=t.goBackwards!==!0;let n={};if(n.className=e.layer.getClassName(),n.config=t,this.backwardLayer=Qr(n),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?sQ:e.mergeMode,nQ(this.mergeMode),e.weights)throw new Se("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,o=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,o)),this.backwardLayer.setWeights(e.slice(o))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let o,n,s;return this.returnState&&(s=t.slice(1)),o=t[0],o=o,this.mergeMode==="concat"?(o[o.length-1]*=2,n=[o]):this.mergeMode==null?n=[o,o.slice()]:n=[o],this.returnState?this.mergeMode==null?n.concat(s).concat(s.slice()):[o].concat(s).concat(s.slice()):xr(n)}apply(e,t){let o=t==null?null:t.initialState,n=t==null?null:t.constants;t==null&&(t={});let s=ZC(e,o,n,this.numConstants);if(e=s.inputs,o=s.initialState,n=s.constants,Array.isArray(e)&&(o=e.slice(1),e=e[0]),(o==null||o.length===0)&&n==null)return super.apply(e,t);let a=[],i=[];if(o!=null){let u=o.length;if(u%2>0)throw new z("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=o,a.push(...o);let c=o.map(p=>new St({shape:p.shape}));this.forwardLayer.stateSpec=c.slice(0,u/2),this.backwardLayer.stateSpec=c.slice(u/2),i.push(...c)}if(n!=null)throw new Se("Support for constants in Bidirectional layers is not implemented yet.");let l=a[0]instanceof Vr;for(let u of a)if(u instanceof Vr!==l)throw new z("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(l){let u=[e].concat(a),c=this.inputSpec.concat(i),p=this.inputSpec;this.inputSpec=c;let m=super.apply(u,t);return this.inputSpec=p,m}else return super.apply(e,t)}call(e,t){return V(()=>{let o=t.initialState,n,s;if(o==null)n=this.forwardLayer.call(e,t),s=this.backwardLayer.call(e,t);else{let l=o.slice(0,o.length/2),u=o.slice(o.length/2);n=this.forwardLayer.call(e,Object.assign(t,{initialState:l})),s=this.backwardLayer.call(e,Object.assign(t,{initialState:u}))}let a;this.returnState&&(Array.isArray(n)&&(a=n.slice(1).concat(s.slice(1))),n=n[0],s=s[0]),this.returnSequences&&(s=qt(s,1));let 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n=C("strides",r,e,t),o=sh(r,e,t),s=C("dataFormat",r,e,t).toUpperCase(),a=C("dilations",r,e,t);return[Kr(C("x",r,e,t),C("filter",r,e,t),[n[1],n[2]],o,s,[a[1],a[2]])]}case"_FusedConv2D":{let{stride:n,pad:o,dataFormat:s,dilations:a,biasArg:i,preluArg:l,activationFunc:u,leakyreluAlpha:c}=bz(r,e,t);return[Go.conv2d({x:C("x",r,e,t),filter:C("filter",r,e,t),strides:[n[1],n[2]],pad:o,dataFormat:s,dilations:[a[1],a[2]],bias:i,activation:u,preluActivationWeights:l,leakyreluAlpha:c})]}case"FusedDepthwiseConv2dNative":{let{stride:n,pad:o,dataFormat:s,dilations:a,biasArg:i,preluArg:l,activationFunc:u,leakyreluAlpha:c}=bz(r,e,t);return[Go.depthwiseConv2d({x:C("x",r,e,t),filter:C("filter",r,e,t),strides:[n[1],n[2]],pad:o,dataFormat:s,dilations:[a[1],a[2]],bias:i,activation:u,preluActivationWeights:l,leakyreluAlpha:c})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let 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this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function U0(r,e,t,n){let o=new Set,s=[],a=null,i=null,l=new Set,u=Object.keys(r).map(m=>en(m)[0]),c=[];n!=null&&(c=n.map(m=>en(m.name)[0]));let p=[...e];for(;p.length>0;){let m=p.pop();if((j0(m)||Ste(m)||Tte(m))&&a==null&&(a=m,i=a.children.map(f=>f.name).filter(f=>o.has(f))),o.add(m.name),t[m.name]==null&&u.indexOf(m.name)===-1&&c.indexOf(m.name)===-1){if(m.inputs.length===0){s.push(m.name);continue}m.inputs.forEach(f=>{l.has(f.name)||(l.add(f.name),p.push(f))})}}return{inputs:r,outputs:e,usedNodes:o,missingInputs:s,dynamicNode:a,syncInputs:i}}function Fz(r,e,t){let{usedNodes:n,inputs:o}=t,s=[],a=Object.keys(o).map(c=>en(c)[0]).map(c=>r.nodes[c]),i=r.initNodes;a.forEach(c=>{n.has(c.name)&&s.push(c)}),r.weights.forEach(c=>{n.has(c.name)&&s.push(c)}),i!=null&&i.forEach(c=>{n.has(c.name)&&s.push(c)});let l=new Set,u=[];for(;s.length>0;){let c=s.pop();l.add(c.name),e[c.name]||u.push(c),c.children.forEach(p=>{!l.has(p.name)&&n.has(p.name)&&p.inputs.every(m=>l.has(m.name))&&s.push(p)})}return u}var Ate=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],Ete=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],Dte=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function j0(r){return Ate.indexOf(r.op)>=0}function Ste(r){return Ete.indexOf(r.op)>=0}function Tte(r){return Dte.indexOf(r.op)>=0}var Jp=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 Jp(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(o=>o.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 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c}processChildNodes(e,t,n,o,s,a){e.children.forEach(i=>{let[l]=Gs(i.name,n);s[l]||!a.has(i.name)||(i.op==="Merge"?i.inputNames.some(u=>!!yr(u,o,n))&&(s[l]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(u=>!!yr(u,o,n))&&(s[l]=!0,t.push({contexts:n.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[o]=en(t),s=this.graph.nodes[o];if(s.attrParams.shape&&s.attrParams.shape.value){let a=s.attrParams.shape.value,i=a.length===n.shape.length&&n.shape.every((l,u)=>a[u]===-1||a[u]===l);y.assert(i,()=>`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&&y.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 ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let o=this._signature.inputs[n];t[o.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[o]=en(n);return this.graph.nodes[o]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${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]=en(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}};var H0=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in 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t=Ir.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(Ir.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${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 o=Ir.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new 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RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(let t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);let e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),n}};var Qp=class extends ih{constructor(){super(Qp.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){let e=this.capacity*2,t=new Array(e),n=this.length();for(let o=0;o<n;o++)t[o]=this.get(this.wrap(this.begin+o));this.data=t,this.capacity=e,this.doubledCapacity=2*this.capacity,this.begin=0,this.end=n}};Qp.INITIAL_CAPACITY=32;function tI(r){return new o3(r)}function ah(r){return new s3(r)}function i3(r,e){return new rI(r,e)}function l3(r,e=ja.FAIL){return new a3(r,e)}var Kt=class{async toArray(){let e=[],t=await this.next();for(;!t.done;)e.push(t.value),t=await this.next();return e}async toArrayForTest(){let e=this.prefetch(100),t=[],n=await e.next();for(;!n.done;)t.push(n.value),n=await e.next();return t}async resolveFully(){let e=await this.next();for(;!e.done;)e=await this.next()}async resolveWhile(e){let t=await this.next(),n=e(t.value);for(;!t.done&&n;)t=await this.next(),n=e(t.value)}handleErrors(e){return new h3(this,e)}filter(e){return new f3(this,e)}map(e){return new d3(this,e)}mapAsync(e){return new nI(this,e)}serialMapAsync(e){return new nI(this,e).serial()}flatmap(e){return new g3(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new m3(this,e,t)}columnMajorBatch(e,t=!0,n=eI){return this.rowMajorBatch(e,t).map(s=>e3(s,n))}concatenate(e,t){return new rI(tI([this,e]),t)}take(e){return e<0||e==null?this:new p3(this,e)}skip(e){return e<0||e==null?this:new c3(this,e)}prefetch(e){return new oI(this,e)}shuffle(e,t){return new x3(this,e,t)}serial(){return new u3(this)}},o3=class extends Kt{constructor(e){super();this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:r3(e),done:!1}}},s3=class extends Kt{constructor(e){super();this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},u3=class extends Kt{constructor(e){super();this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},c3=class extends Kt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;Ae(e.value)}return this.upstream.next()}},p3=class extends Kt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},m3=class extends Kt{constructor(e,t,n=!0){super();this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},f3=class extends Kt{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Ae(e.value)}}},d3=class extends Kt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Mo.getTensorsInContainer(e.value),n=this.transform(e.value),o=Mo.getTensorsInContainer(n);for(let s of t)Mo.isTensorInList(s,o)||s.dispose();return{value:n,done:!1}}},h3=class extends Kt{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},nI=class extends Kt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Mo.getTensorsInContainer(e.value),n=await this.transform(e.value),o=Mo.getTensorsInContainer(n);for(let s of t)Mo.isTensorInList(s,o)||s.dispose();return{value:n,done:!1}}},em=class extends Kt{constructor(){super();this.outputQueue=new Qp,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},g3=class extends em{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=Mo.getTensorsInContainer(e.value),n=this.transform(e.value),o=Mo.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let s of t)Mo.isTensorInList(s,o)||s.dispose();return!0}},rI=class extends Kt{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}},ja;(function(r){r[r.FAIL=0]="FAIL",r[r.SHORTEST=1]="SHORTEST",r[r.LONGEST=2]="LONGEST"})(ja||(ja={}));var a3=class extends Kt{constructor(e,t=ja.FAIL){super();this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function o(a){return a instanceof Kt?{value:a.next().then(l=>(t++,l.done&&n++,l.value)),recurse:!1}:{value:null,recurse:!0}}let s=await iy(this.iterators,o);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case ja.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case ja.SHORTEST:return{value:null,done:!0};case ja.LONGEST:default:}return this.count++,{value:s,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},oI=class extends Kt{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new ih(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},x3=class extends oI{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=n3.alea(n||y.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}};var Ki=class{constructor(){this.size=null}batch(e,t=!0){let n=this;y.assert(e>0,()=>`batchSize needs to be positive, but it is
-      ${e}`);let o;return this.size===Infinity||this.size==null?o=this.size:t?o=Math.ceil(this.size/e):o=Math.floor(this.size/e),gn(async()=>(await n.iterator()).columnMajorBatch(e,t,Gte),o)}concatenate(e){let t=this,n;return this.size===Infinity||e.size===Infinity?n=Infinity:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,gn(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===Infinity?n=Infinity:n=null,gn(async()=>(await t.iterator()).filter(o=>G(()=>e(o))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return gn(async()=>(await t.iterator()).map(n=>G(()=>e(n))),this.size)}mapAsync(e){let t=this;return gn(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return gn(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=Infinity:n=null,gn(async()=>{let o=ah(async()=>({value:await t.iterator(),done:!1}));return i3(o.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,gn(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let o=this,s=y3.alea(t||y.now().toString());return gn(async()=>{let a=s.int32();return n&&(a+=s.int32()),(await o.iterator()).shuffle(e,a.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,gn(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Ki.MAX_BUFFER_SIZE=1e4;function gn(r,e=null){return new class extends Ki{constructor(){super(...arguments);this.size=e}async iterator(){return r()}}}function b3(r){return gn(async()=>tI(r),r.length)}function w3(r){if(!El(r))throw new Error("The argument to zip() must be an object or array.");let e;if(Array.isArray(r))for(let t=0;t<r.length;t++)e=e==null?r[t].size:Math.min(e,r[t].size);else if(r instanceof Object)for(let t in r)e=e==null?r[t].size:Math.min(e,r[t].size);return gn(async()=>{let t=await iy(r,n=>{if(n instanceof Ki)return{value:n.iterator(),recurse:!1};if(El(n))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return l3(t,ja.SHORTEST)},e)}function Gte(r){if(r===null)return null;let e=r[0];return t3(e)?{value:Wte(r),recurse:!1}:{value:null,recurse:!0}}function Wte(r){if(r.length===0)throw new Error("Can't make a batch of zero elements.");return r[0]instanceof Ve?Vt(r):Rr(r)}var lh=class extends Ki{constructor(e){super();this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
-`).map(o=>(o.endsWith("\r")&&(o=o.slice(0,-1)),o))}};var ay='"',uh=Symbol("out"),k3=Symbol("field"),ly=Symbol("quote"),sI=Symbol("quoteafterquote"),_3=Symbol("quoteinquote"),ch=class extends Ki{constructor(e,t){super();this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new lh(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(y.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&y.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((o,s)=>(o[s]=o[s]+1||1,o),{}),n=Object.keys(t).filter(o=>t[o]>1);if(y.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let o of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(o)===-1)throw new Error('The key "'+o+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let t=await(await this.base.iterator()).next();if(t.done)throw new Error("No data was found for CSV parsing.");let n=t.value;return this.parseRow(n,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},o={};for(let s=0;s<this.fullColumnNames.length;s++){let a=this.fullColumnNames[s],i=this.columnConfigs?this.columnConfigs[a]:null;if(!(this.configuredColumnsOnly&&!i)){let l=t[s],u=null;if(l==="")if(i&&i.default!==void 0)u=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${a} is empty in this line: ${e}`);u=void 0}else{let c=Number(l);if(isNaN(c))i&&i.dtype==="bool"?u=this.getBoolean(l):u=l;else if(!i||!i.dtype)u=c;else switch(i.dtype){case"float32":u=c;break;case"int32":u=Math.floor(c);break;case"bool":u=this.getBoolean(l);break;default:u=c}}i&&i.isLabel?o[a]=u:n[a]=u}}return Object.keys(o).length===0?n:{xs:n,ys:o}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],o=0,s=e.length,a=uh;for(let i=0;i<s;i++)switch(a){case uh:switch(e.charAt(i)){case ay:o=i+1,a=ly;break;case this.delimiter:if(o=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),a=uh;break;default:a=k3,o=i;break}break;case k3:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(o,i)),a=uh,o=i+1;break;default:}break;case ly:switch(e.charAt(i)){case ay:a=sI;break;default:}break;case sI:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(o,i-1)),a=uh,o=i+1;break;case ay:a=ly;break;default:a=_3;break}break;case _3:switch(e.charAt(i)){case ay:a=ly;break;default:}break;default:}if(a===sI?n.push(e.substring(o,s-1)):n.push(e.substring(o)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}};var ph=class extends Kt{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(j().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new ph(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 o=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(o,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let o=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(o,[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(o=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&o({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),o({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((o,s)=>n.set(o,s*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(y.sizeFromShape(t));return n.set(e,n.length-e.length),Rr(n,t)}};var mh=class extends Kt{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=Gt([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,o=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-n)/2,a=(1-o)/2,i=s+n,l=o+a;this.cropBox=Li([a,s,l,i],[1,4])}else this.cropBox=Li([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(j().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new mh(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&y.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=Yh.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return G(()=>{let t=ar(oe(e,"float32"),0),n;n=$s.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let o=n.shape;return L(n,o.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.")}};var fh=class{};var uy=class extends Kt{split(e){return new v3(this,e)}},v3=class extends uy{constructor(e,t){super();this.upstream=e,this.impl=new C3(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},C3=class extends em{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}};var iI=class extends Kt{decodeUTF8(){return new N3(this)}},N3=class extends uy{constructor(e){super();this.upstream=e,this.impl=new S3(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},S3=class extends em{constructor(e){super();if(this.upstream=e,j().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=I3();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return j().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}};var dh=class extends iI{constructor(e,t={}){super();this.file=e,this.options=t,y.assert(e instanceof Uint8Array||(j().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((t,n)=>{let o=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)t(new Uint8Array(this.file.slice(this.offset,o)));else{let s=new FileReader;s.onload=i=>{let l=s.result;if(l instanceof ArrayBuffer&&(l=new Uint8Array(l)),!(l instanceof Uint8Array))return n(new TypeError("FileReader returned unknown type."));t(l)},s.onabort=i=>n(new Error("Aborted")),s.onerror=i=>n(new Error(i.type));let a=this.file.slice(this.offset,o);s.readAsArrayBuffer(a)}this.offset=o}),done:!1}}};async function T3(r,e={}){let t,n;typeof r=="string"?t=r:(t=r.url,n=jte(r));let o=await y.fetch(t,n);if(o.ok){let s=new Uint8Array(await o.arrayBuffer());return new dh(s,e)}else throw new Error(o.statusText)}var jte=r=>({method:r.method,headers:r.headers,body:r.body,mode:r.mode,credentials:r.credentials,cache:r.cache,redirect:r.redirect,referrer:r.referrer,integrity:r.integrity});function cy(r){return typeof r=="string"&&r.substr(0,7)==="file://"}var hh=class extends fh{constructor(e,t={}){super();this.input=e,this.options=t}async iterator(){if(cy(this.input)&&j().get("IS_NODE")){let e=require("fs");this.input=e.readFileSync(this.input.substr(7))}return new dh(this.input,this.options)}};var gh=class extends fh{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return cy(this.url)?new hh(this.url,this.fileOptions).iterator():T3(this.url,this.fileOptions)}};function A3(r,e={}){return new ch(new gh(r),e)}function E3(r){let e=ah(r);return gn(async()=>e)}function D3(r){return gn(async()=>{let e=await r();return ah(()=>e.next())})}async function $3(r,e){return mh.create(r,e)}async function R3(r){return ph.create(r)}var F3="3.3.0";var Ute={tfjs:bI,"tfjs-core":wI,"tfjs-data":kI,"tfjs-layers":_I,"tfjs-converter":vI,"tfjs-backend-cpu":bk,"tfjs-backend-webgl":O_,"tfjs-backend-wasm":xC};export{as as Abs,qs as Acos,Ks as Acosh,np as AdadeltaOptimizer,op as AdagradOptimizer,sp as AdamOptimizer,ip as AdamaxOptimizer,wn as Add,Hn as AddN,Ml as All,Ll as Any,qn as ArgMax,ea as ArgMin,Xs as Asin,Ys as Asinh,Zs as Atan,Qs as Atan2,Js as Atanh,Kn as AvgPool,ta as AvgPool3D,Bl as AvgPool3DGrad,zl as AvgPoolGrad,sx as BackendWasm,Xn as BatchMatMul,ra as BatchToSpaceND,Vl as Bincount,Ob as BroadcastTo,zx as Callback,kx as CallbackList,$n as Cast,Yn as Ceil,Rn as ClipByValue,Gl as Complex,na as ComplexAbs,ls as Concat,Zn as Conv2D,Wl as Conv2DBackpropFilter,Jn as Conv2DBackpropInput,oa as Conv3D,jl as Conv3DBackpropFilterV2,Ul as Conv3DBackpropInputV2,Qn as Cos,ei as Cosh,ti as CropAndResize,eo as Cumsum,vx as CustomCallback,Za as DataStorage,Hl as DenseBincount,ri as DepthToSpace,to as DepthwiseConv2dNative,ql as DepthwiseConv2dNativeBackpropFilter,Kl as DepthwiseConv2dNativeBackpropInput,Xl as Diag,sa as Dilation2D,Pc as Dilation2DBackpropFilter,Oc as Dilation2DBackpropInput,$b as ENV,Vx as EarlyStopping,ni as Elu,Yl as EluGrad,Bh as Environment,si as Equal,oi as Erf,no as Exp,us as ExpandDims,ii as Expm1,Zl as FFT,ia as Fill,ai as FlipLeftRight,oo as Floor,so as FloorDiv,Mc as FromPixels,io as FusedBatchNorm,ks as FusedConv2D,_s as FusedDepthwiseConv2D,zg as GPGPUContext,li as GatherNd,cs as GatherV2,ny as GraphModel,ui as Greater,ao as GreaterEqual,_x as History,Jl as IFFT,Fn as Identity,Ql as Imag,Tt as InputSpec,ci as IsFinite,pi as IsInf,mi as IsNan,js as KernelBackend,aa as LRN,tu as LRNGrad,Yf as LayerVariable,Tn as LayersModel,lo as LeakyRelu,fi as Less,di as LessEqual,eu as LinSpace,uo as Log,hi as Log1p,Pb as LogSoftmax,gi as LogicalAnd,Ja as LogicalNot,Qa as LogicalOr,Hu as MathBackendCPU,Ju as MathBackendWebGL,co as Max,mo as MaxPool,la as MaxPool3D,nu as MaxPool3DGrad,ru as MaxPoolGrad,ou as MaxPoolWithArgmax,po as Maximum,fo as Mean,ho as Min,go as Minimum,ua as MirrorPad,xi as Mod,ap as MomentumOptimizer,su as Multinomial,xo as Multiply,ps as Neg,bi as NonMaxSuppressionV3,wi as NonMaxSuppressionV4,ki as NonMaxSuppressionV5,yi as NotEqual,GI as OP_SCOPE_SUFFIX,yo as OneHot,ms as OnesLike,Pr as Optimizer,fs as Pack,bo as PadV2,tV as Pool,wo as Pow,ko as Prelu,_i as Prod,lp as RMSPropOptimizer,hn as RNN,ca as Range,Vb as Rank,iu as Real,ro as RealDiv,vi as Reciprocal,Wt as Reduction,_o as Relu,Co as Relu6,ds as Reshape,vo as ResizeBilinear,lu as ResizeBilinearGrad,pa as ResizeNearestNeighbor,au as ResizeNearestNeighborGrad,Io as Reverse,$i as RotateWithOffset,No as Round,So as Rsqrt,ul as SGDOptimizer,Ci as ScatterNd,hs as Select,Ii as Selu,qi as Sequential,Ao as Sigmoid,Si as Sign,To as Sin,Ni as Sinh,gs as Slice,$o as Softmax,Ti as Softplus,ma as SpaceToBatchND,uu as SparseToDense,xs as SplitV,Eo as Sqrt,fa as Square,Ro as SquaredDifference,On as Step,Ai as StridedSlice,Fo as Sub,Do as Sum,Vr as SymbolicTensor,Ei as Tan,Oo as Tanh,Ve as Tensor,lt as TensorBuffer,kn as Tile,Di as TopK,cu as Transform,Po as Transpose,pu as Unique,ys as Unpack,da as UnsortedSegmentSum,rl as Variable,bs as ZerosLike,ws as _FusedMatMul,Nt as abs,_m as acos,vm as acosh,ee as add,gw as addN,bu as all,sl as any,il as argMax,Cm as argMin,Im as asin,Nm as asinh,Sm as atan,Tm as atan2,Am as atanh,wa as avgPool,Em as avgPool3d,hw as backend,S as backend_util,oW as basicLSTMCell,Lo as batchNorm,ww as batchNorm2d,kw as batchNorm3d,_w as batchNorm4d,ka as batchToSpaceND,vw as bincount,mU as booleanMaskAsync,al as broadcastTo,Yh as browser,ve as buffer,nz as callbacks,oe as cast,Dm as ceil,ir as clipByValue,Pn as clone,_n as complex,Ze as concat,Cw as concat1d,Iw as concat2d,Nw as concat3d,Sw as concat4d,NC as constraints,_u as conv1d,Kr as conv2d,vu as conv2dTranspose,$m as conv3d,IW as conv3dTranspose,oV as copyRegisteredKernels,_a as cos,Cu as cosh,rf as cosineWindow,Iu as cumsum,Xr as customGrad,py as data,Tw as denseBincount,rg as deprecationWarn,Rm as depthToSpace,Is as depthwiseConv2d,iz as deregisterOp,hu as device_util,RW as diag,Fm as dilation2d,xG as disableDeprecationWarnings,Ae as dispose,yG as disposeVariables,me as div,Om as divNoNan,Aw as dot,tk as dropout,Ns as elu,gG as enableDebugMode,hG as enableProdMode,rk as enclosingPowerOfTwo,Mn as engine,j as env,vn as equal,Pm as erf,Zt as exp,ar as expandDims,Mm as expm1,Yc as eye,Ea as fft,va as fill,CG as findBackend,IG as findBackendFactory,Ss as floor,yu as floorDiv,P_ as forceHalfFloat,Go as fused,zo as gather,ek as gatherND,Zh as gather_util,_G as getBackend,Vh as getGradient,zc as getKernel,gm as getKernelsForBackend,fE as gpgpu_util,lj as grad,uj as grads,er as greater,an as greaterEqual,Mi as ifft,Nu as imag,$s as image,kU as inTopKAsync,DC as initializers,Mx as input,Ir as io,Lu as irfft,Ew as isFinite,Dw as isInf,$w as isNaN,Dt as keep,Ar as kernel_impls,f0 as layers,Ca as leakyRelu,Su as less,Bn as lessEqual,ak as linalg,Rw as linspace,Oz as loadGraphModel,jL as loadLayersModel,Lm as localResponseNormalization,lr as log,Tu as log1p,Fw as logSigmoid,Au as logSoftmax,Bm as logSumExp,hr as logicalAnd,Ia as logicalNot,Eu as logicalOr,Lw as logicalXor,dH as losses,We as matMul,bN as math,ur as max,Na as maxPool,Vm as maxPool3d,zw as maxPoolWithArgmax,Yr as maximum,ht as mean,qc as memory,x0 as metrics,Pi as min,As as minimum,Gm as mirrorPad,Wm as mod,GL as model,y0 as models,Zc as moments,hU as movingAverage,P as mul,Lj as multiRNNCell,Bw as multinomial,He as neg,nf as nextFrame,Vu as norm,Vo as notEqual,Cs as oneHot,Nr as ones,tr as onesLike,T as op,Wj as outerProduct,Fr as pad,Hj as pad1d,Kj as pad2d,Yj as pad3d,Jj as pad4d,Vw as pool,Or as pow,Ta as prelu,sw as print,Du as prod,bG as profile,a4 as rand,h4 as randomGamma,cg as randomNormal,Es as randomUniform,Qc as range,kG as ready,ll as real,jm as reciprocal,xu as registerBackend,UL as registerCallbackConstructor,Lb as registerGradient,el as registerKernel,sz as registerOp,b0 as regularizers,Sr as relu,Ru as relu6,vG as removeBackend,L as reshape,qt as reverse,C4 as reverse1d,N4 as reverse2d,T4 as reverse3d,E4 as reverse4d,Da as rfft,Um as round,Fu as rsqrt,le as scalar,Qw as scatterND,Jh as scatter_util,Ou as selu,Hm as separableConv2d,WL as sequential,Q as serialization,PN as setBackend,NG as setPlatform,ZZ as setWasmPath,JZ as setWasmPaths,Bk as setWebGLContext,Yw as setdiff1dAsync,wg as shared,qr as sigmoid,qm as sign,fH as signal,Pu as sin,Mu as sinh,Re as slice,Km as slice1d,pg as slice2d,Xm as slice3d,ep as slice4d,sr as slice_util,Aa as softmax,Ts as softplus,Sa as spaceToBatchND,tf as sparseToDense,mH as spectral,cr as split,xt as sqrt,Oe as square,zu as squaredDifference,Cn as squeeze,Vt as stack,Ds as step,Ym as stridedSlice,ce as sub,ge as sum,fu as sumOutType,Zm as tan,Oi as tanh,Rr as tensor,Gt as tensor1d,Li as tensor2d,uw as tensor3d,rU as tensor4d,nU as tensor5d,oU as tensor6d,Mo as tensor_util,RN as test_util,G as tidy,zn as tile,wG as time,Jm as topk,cl as train,Ue as transpose,Bu as truncatedNormal,tp as unique,nV as unregisterGradient,rV as unregisterKernel,Qm as unsortedSegmentSum,pr as unstack,dr as upcastType,y as util,cj as valueAndGrad,pj as valueAndGrads,Zw as variable,ig as variableGrads,Ute as version,Pz as version_converter,dG as version_core,bk as version_cpu,Wp as version_layers,xC as version_wasm,O_ as version_webgl,r8 as webgl,lE as webgl_util,$t as where,ef as whereAsync,gt as zeros,Ce as zerosLike};
+        ${o}, and tensor's shape is: ${r.shape}`);let s=r.shape.slice(1),a=Jx(s,t),i=o===0?0:r.size/o,l=V(()=>{let c=[];r=L(r,[1,o,i]);for(let p=0;p<e.length;++p){let m=p===0?0:n[p-1],f=[0,m,0],d=[1,e[p],i];c[p]=L(Re(r,f,d),a)}return r.dispose(),c}),u=new hc([],t,r.dtype,e.length);for(let c=0;c<l.length;c++)u.setItem(c,l[c]);return u}var XL=async(r,e,t)=>{switch(r.op){case"If":case"StatelessIf":{let o=C("thenBranch",r,e,t),n=C("elseBranch",r,e,t),s=C("cond",r,e,t),a=C("args",r,e,t);return(await s.data())[0]?t.functionMap[o].executeFunctionAsync(a,t.tensorArrayMap,t.tensorListMap):t.functionMap[n].executeFunctionAsync(a,t.tensorArrayMap,t.tensorListMap)}case"While":case"StatelessWhile":{let o=C("body",r,e,t),n=C("cond",r,e,t),s=C("args",r,e,t),a=await t.functionMap[n].executeFunctionAsync(s,t.tensorArrayMap,t.tensorListMap),i=s.map(c=>c.id),l=await a[0].data();a.forEach(c=>{!c.kept&&i.indexOf(c.id)===-1&&c.dispose()});let u=s;for(;l[0];){let c=u;u=await t.functionMap[o].executeFunctionAsync(u,t.tensorArrayMap,t.tensorListMap);let p=u.map(f=>f.id);c.forEach(f=>{!f.kept&&i.indexOf(f.id)===-1&&p.indexOf(f.id)===-1&&f.dispose()});let m=await t.functionMap[n].executeFunctionAsync(u,t.tensorArrayMap,t.tensorListMap);l=await m[0].data(),m.forEach(f=>{!f.kept&&i.indexOf(f.id)===-1&&p.indexOf(f.id)===-1&&f.dispose()})}return u}case"LoopCond":{let o=C("pred",r,e,t);return[Ws(o)]}case"Switch":{let o=C("pred",r,e,t),n=C("data",r,e,t);return n.kept||(n=Ws(n)),(await o.data())[0]?[void 0,n]:[n,void 0]}case"Merge":{let o=r.inputNames.find(n=>yr(n,e,t)!==void 0);if(o){let n=yr(o,e,t);return[Ws(n)]}return}case"Enter":{let o=C("frameName",r,e,t),n=C("tensor",r,e,t);return t.enterFrame(o),[Ws(n)]}case"Exit":{let o=C("tensor",r,e,t);return t.exitFrame(),[Ws(o)]}case"NextIteration":{let o=C("tensor",r,e,t);return t.nextIteration(),[Ws(o)]}case"TensorArrayV3":{let 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cz=(r,e,t)=>{switch(r.op){case"Cast":return[ne(C("x",r,e,t),C("dtype",r,e,t))];case"ExpandDims":{let o=C("axis",r,e,t);return[ar(C("x",r,e,t),o)]}case"Squeeze":{let o=C("axis",r,e,t);return[Co(C("x",r,e,t),o)]}case"Reshape":return[L(C("x",r,e,t),C("shape",r,e,t))];case"MirrorPad":return[Vm(C("x",r,e,t),C("padding",r,e,t),C("mode",r,e,t))];case"PadV2":case"Pad":return[Fr(C("x",r,e,t),C("padding",r,e,t),C("constantValue",r,e,t))];case"SpaceToBatchND":{let o=C("blockShape",r,e,t),n=C("paddings",r,e,t);return[Sa(C("x",r,e,t),o,n)]}case"BatchToSpaceND":{let o=C("blockShape",r,e,t),n=C("crops",r,e,t);return[ka(C("x",r,e,t),o,n)]}case"DepthToSpace":{let o=C("blockSize",r,e,t),n=C("dataFormat",r,e,t).toUpperCase();return[$m(C("x",r,e,t),o,n)]}case"BroadcastTo":return[al(C("x",r,e,t),C("shape",r,e,t))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};function P0(r,e,t,o){let n=((s,a,i)=>{switch(s.category){case"arithmetic":return V(()=>GL(s,a,i));case"basic_math":return V(()=>WL(s,a,i));case"control":return XL(s,a,i);case"convolution":return V(()=>ZL(s,a,i));case"creation":return V(()=>JL(s,a,i));case"dynamic":return QL(s,a,i);case"evaluation":return V(()=>ez(s,a,i));case"image":return V(()=>oz(s,a,i));case"graph":return V(()=>tz(s,a,i));case"logical":return V(()=>nz(s,a,i));case"matrices":return V(()=>sz(s,a,i));case"normalization":return V(()=>iz(s,a,i));case"reduction":return V(()=>az(s,a,i));case"slice_join":return V(()=>lz(s,a,i));case"spectral":return V(()=>uz(s,a,i));case"transformation":return V(()=>cz(s,a,i));case"hash_table":return rz(s,a,i,o);case"custom":let l=zx(s.op);if(l&&l.customExecutor)return l.customExecutor(new $0(s,a,i));throw TypeError(`Custom op ${s.op} is not registered.`);default:throw TypeError(`Unknown op '${s.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 L0(r,e,t,o){let n=new Set,s=[],a=null,i=null,l=new Set,u=Object.keys(r).map(m=>eo(m)[0]),c=[];o!=null&&(c=o.map(m=>eo(m.name)[0]));let p=[...e];for(;p.length>0;){let m=p.pop();if((M0(m)||Jee(m)||Qee(m))&&a==null&&(a=m,i=a.children.map(f=>f.name).filter(f=>n.has(f))),n.add(m.name),t[m.name]==null&&u.indexOf(m.name)===-1&&c.indexOf(m.name)===-1){if(m.inputs.length===0){s.push(m.name);continue}m.inputs.forEach(f=>{l.has(f.name)||(l.add(f.name),p.push(f))})}}return{inputs:r,outputs:e,usedNodes:n,missingInputs:s,dynamicNode:a,syncInputs:i}}function pz(r,e,t){let{usedNodes:o,inputs:n}=t,s=[],a=Object.keys(n).map(c=>eo(c)[0]).map(c=>r.nodes[c]),i=r.initNodes;a.forEach(c=>{o.has(c.name)&&s.push(c)}),r.weights.forEach(c=>{o.has(c.name)&&s.push(c)}),i!=null&&i.forEach(c=>{o.has(c.name)&&s.push(c)});let l=new Set,u=[];for(;s.length>0;){let c=s.pop();l.add(c.name),e[c.name]||u.push(c),c.children.forEach(p=>{!l.has(p.name)&&o.has(p.name)&&p.inputs.every(m=>l.has(m.name))&&s.push(p)})}return u}var ete=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],tte=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],rte=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function M0(r){return ete.indexOf(r.op)>=0}function Jee(r){return tte.indexOf(r.op)>=0}function Qee(r){return rte.indexOf(r.op)>=0}var Zp=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(o=>{this._functionExecutorMap[o]=new Zp(e.functions[o],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(o=>e[o].map(n=>n.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 o=e.map(s=>s.name).sort(),n=t.map(s=>s.name).sort();return o.join(this.SEPERATOR)+"--"+n.join(this.SEPERATOR)}compile(e,t){let o=L0(e,t,this.weightMap,this._initNodes),{missingInputs:n,dynamicNode:s,syncInputs:a}=o;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. 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c}processChildNodes(e,t,o,n,s,a){e.children.forEach(i=>{let[l]=Gs(i.name,o);s[l]||!a.has(i.name)||(i.op==="Merge"?i.inputNames.some(u=>!!yr(u,n,o))&&(s[l]=!0,t.push({contexts:o.currentContext,node:i})):i.inputNames.every(u=>!!yr(u,n,o))&&(s[l]=!0,t.push({contexts:o.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let o=e[t],[n]=eo(t),s=this.graph.nodes[n];if(s.attrParams.shape&&s.attrParams.shape.value){let a=s.attrParams.shape.value,i=a.length===o.shape.length&&o.shape.every((l,u)=>a[u]===-1||a[u]===l);y.assert(i,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${a}], but was [${o.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&y.assert(o.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${o.dtype}`)})}mapInputs(e){let t={};for(let o 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Mismatched at element ${this.count}.`);case ja.SHORTEST:return{value:null,done:!0};case ja.LONGEST:default:}return this.count++,{value:s,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},Z0=class extends Kt{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new sh(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},Kz=class extends Z0{constructor(e,t,o){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=Fz.alea(o||y.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}};var Ki=class{constructor(){this.size=null}batch(e,t=!0){let o=this;y.assert(e>0,()=>`batchSize needs to be positive, but it is
+      ${e}`);let n;return this.size===Infinity||this.size==null?n=this.size:t?n=Math.ceil(this.size/e):n=Math.floor(this.size/e),go(async()=>(await o.iterator()).columnMajorBatch(e,t,fte),n)}concatenate(e){let t=this,o;return this.size===Infinity||e.size===Infinity?o=Infinity:this.size!=null&&e.size!=null?o=this.size+e.size:o=null,go(async()=>(await t.iterator()).concatenate(await e.iterator()),o)}filter(e){let t=this,o;return this.size===Infinity?o=Infinity:o=null,go(async()=>(await t.iterator()).filter(n=>V(()=>e(n))),o)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return go(async()=>(await t.iterator()).map(o=>V(()=>e(o))),this.size)}mapAsync(e){let t=this;return go(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return go(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,o;return this.size!=null&&e>0?o=this.size*e:e===0?o=0:this.size!=null&&(e===void 0||e<0)?o=Infinity:o=null,go(async()=>{let n=ih(async()=>({value:await t.iterator(),done:!1}));return Mz(n.take(e))},o)}skip(e){let t=this,o;return this.size!=null&&e>=0&&this.size>=e?o=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?o=0:o=null,go(async()=>(await t.iterator()).skip(e),o)}shuffle(e,t,o=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let n=this,s=Xz.alea(t||y.now().toString());return go(async()=>{let a=s.int32();return o&&(a+=s.int32()),(await n.iterator()).shuffle(e,a.toString())},this.size)}take(e){let t=this,o;return this.size!=null&&this.size>e?o=e:this.size!=null&&this.size<=e?o=this.size:o=null,go(async()=>(await t.iterator()).take(e),o)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Ki.MAX_BUFFER_SIZE=1e4;function go(r,e=null){return new class extends Ki{constructor(){super(...arguments);this.size=e}async iterator(){return r()}}}function Yz(r){return go(async()=>K0(r),r.length)}function Zz(r){if(!El(r))throw new Error("The argument to zip() must be an object or array.");let e;if(Array.isArray(r))for(let t=0;t<r.length;t++)e=e==null?r[t].size:Math.min(e,r[t].size);else if(r instanceof Object)for(let t in r)e=e==null?r[t].size:Math.min(e,r[t].size);return go(async()=>{let t=await oy(r,o=>{if(o instanceof Ki)return{value:o.iterator(),recurse:!1};if(El(o))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return zz(t,ja.SHORTEST)},e)}function fte(r){if(r===null)return null;let e=r[0];return $z(e)?{value:dte(r),recurse:!1}:{value:null,recurse:!0}}function dte(r){if(r.length===0)throw new Error("Can't make a batch of zero elements.");return r[0]instanceof Ve?Bt(r):Rr(r)}var ah=class extends Ki{constructor(e){super();this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
+`).map(n=>(n.endsWith("\r")&&(n=n.slice(0,-1)),n))}};var ny='"',lh=Symbol("out"),Jz=Symbol("field"),sy=Symbol("quote"),J0=Symbol("quoteafterquote"),Qz=Symbol("quoteinquote"),uh=class extends Ki{constructor(e,t){super();this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new ah(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(y.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&y.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((n,s)=>(n[s]=n[s]+1||1,n),{}),o=Object.keys(t).filter(n=>t[n]>1);if(y.assert(o.length===0,()=>"Duplicate column names found: "+o.toString()),this.columnConfigs){for(let n of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(n)===-1)throw new Error('The key "'+n+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let t=await(await this.base.iterator()).next();if(t.done)throw new Error("No data was found for CSV parsing.");let o=t.value;return this.parseRow(o,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),o={},n={};for(let s=0;s<this.fullColumnNames.length;s++){let a=this.fullColumnNames[s],i=this.columnConfigs?this.columnConfigs[a]:null;if(!(this.configuredColumnsOnly&&!i)){let l=t[s],u=null;if(l==="")if(i&&i.default!==void 0)u=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${a} is empty in this line: ${e}`);u=void 0}else{let c=Number(l);if(isNaN(c))i&&i.dtype==="bool"?u=this.getBoolean(l):u=l;else if(!i||!i.dtype)u=c;else switch(i.dtype){case"float32":u=c;break;case"int32":u=Math.floor(c);break;case"bool":u=this.getBoolean(l);break;default:u=c}}i&&i.isLabel?n[a]=u:o[a]=u}}return Object.keys(n).length===0?o:{xs:o,ys:n}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let o=[],n=0,s=e.length,a=lh;for(let i=0;i<s;i++)switch(a){case lh:switch(e.charAt(i)){case ny:n=i+1,a=sy;break;case this.delimiter:if(n=i+1,this.delimiter===" "&&this.delimWhitespace)break;o.push(""),a=lh;break;default:a=Jz,n=i;break}break;case Jz:switch(e.charAt(i)){case this.delimiter:o.push(e.substring(n,i)),a=lh,n=i+1;break;default:}break;case sy:switch(e.charAt(i)){case ny:a=J0;break;default:}break;case J0:switch(e.charAt(i)){case this.delimiter:o.push(e.substring(n,i-1)),a=lh,n=i+1;break;case ny:a=sy;break;default:a=Qz;break}break;case Qz:switch(e.charAt(i)){case ny:a=sy;break;default:}break;default:}if(a===J0?o.push(e.substring(n,s-1)):o.push(e.substring(n)),t&&o.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${o}`);return o}};var ch=class extends Kt{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(W().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new ch(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(o){throw new Error(`Error thrown while initializing video stream: ${o.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,o=await this.getAudioData();if(this.includeSpectrogram){let n=this.flattenQueue(o.freqDataQueue);e=this.getTensorFromAudioDataArray(n,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let n=this.flattenQueue(o.timeDataQueue);t=this.getTensorFromAudioDataArray(n,[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=[],o=0;return new Promise(n=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&n({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++o===this.numFrames&&(clearInterval(s),n({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,o=new Float32Array(e.length*t);return e.forEach((n,s)=>o.set(n,s*t)),o}getTensorFromAudioDataArray(e,t){let o=new Float32Array(y.sizeFromShape(t));return o.set(e,o.length-e.length),Rr(o,t)}};var ph=class extends Kt{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=Vt([0],"int32"),this.webcamConfig.centerCrop){let o=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,n=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-o)/2,a=(1-n)/2,i=s+o,l=n+a;this.cropBox=Li([a,s,l,i],[1,4])}else this.cropBox=Li([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(W().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 o=new ph(e,t);return await o.start(),o}async start(){this.webcamConfig.facingMode&&y.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=Xh.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: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return V(()=>{let t=ar(ne(e,"float32"),0),o;o=$s.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let n=o.shape;return L(o,n.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.")}};var mh=class{};var iy=class extends Kt{split(e){return new e3(this,e)}},e3=class extends iy{constructor(e,t){super();this.upstream=e,this.impl=new t3(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},t3=class extends Qp{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 o of t.slice(0,-1))this.outputQueue.push(o);return this.carryover=t[t.length-1],!0}};var Q0=class extends Kt{decodeUTF8(){return new o3(this)}},o3=class extends iy{constructor(e){super();this.upstream=e,this.impl=new n3(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},n3=class extends Qp{constructor(e){super();if(this.upstream=e,W().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=r3();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let o;return W().get("IS_BROWSER")?o=this.decoder.decode(t,{stream:!0}):o=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(o),!0}};var fh=class extends Q0{constructor(e,t={}){super();this.file=e,this.options=t,y.assert(e instanceof Uint8Array||(W().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((t,o)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)t(new Uint8Array(this.file.slice(this.offset,n)));else{let s=new FileReader;s.onload=i=>{let l=s.result;if(l instanceof ArrayBuffer&&(l=new Uint8Array(l)),!(l instanceof Uint8Array))return o(new TypeError("FileReader returned unknown type."));t(l)},s.onabort=i=>o(new Error("Aborted")),s.onerror=i=>o(new Error(i.type));let a=this.file.slice(this.offset,n);s.readAsArrayBuffer(a)}this.offset=n}),done:!1}}};async function s3(r,e={}){let t,o;typeof r=="string"?t=r:(t=r.url,o=hte(r));let n=await y.fetch(t,o);if(n.ok){let s=new Uint8Array(await n.arrayBuffer());return new fh(s,e)}else throw new Error(n.statusText)}var hte=r=>({method:r.method,headers:r.headers,body:r.body,mode:r.mode,credentials:r.credentials,cache:r.cache,redirect:r.redirect,referrer:r.referrer,integrity:r.integrity});function ay(r){return typeof r=="string"&&r.substr(0,7)==="file://"}var dh=class extends mh{constructor(e,t={}){super();this.input=e,this.options=t}async iterator(){if(ay(this.input)&&W().get("IS_NODE")){let e=require("fs");this.input=e.readFileSync(this.input.substr(7))}return new fh(this.input,this.options)}};var hh=class extends mh{constructor(e,t={}){super();this.url=e,this.fileOptions=t}async iterator(){return ay(this.url)?new dh(this.url,this.fileOptions).iterator():s3(this.url,this.fileOptions)}};function i3(r,e={}){return new uh(new hh(r),e)}function a3(r){let e=ih(r);return go(async()=>e)}function l3(r){return go(async()=>{let e=await r();return ih(()=>e.next())})}async function u3(r,e){return ph.create(r,e)}async function c3(r){return ch.create(r)}var p3="3.3.0";var gte={tfjs:mI,"tfjs-core":fI,"tfjs-data":dI,"tfjs-layers":hI,"tfjs-converter":gI,"tfjs-backend-cpu":yk,"tfjs-backend-webgl":T_,"tfjs-backend-wasm":cC};export{as as Abs,qs as Acos,Ks as Acosh,rp as AdadeltaOptimizer,op as AdagradOptimizer,np as AdamOptimizer,sp as AdamaxOptimizer,wo as Add,Ho as AddN,Ml as All,Ll as Any,qo as ArgMax,ea as ArgMin,Xs as Asin,Ys as Asinh,Zs as Atan,Qs as Atan2,Js as Atanh,Ko as AvgPool,ta as AvgPool3D,Bl as AvgPool3DGrad,zl as AvgPoolGrad,rx as BackendWasm,Xo as BatchMatMul,ra as BatchToSpaceND,Vl as Bincount,$b as BroadcastTo,Px as Callback,yx as CallbackList,$o as Cast,Yo as Ceil,Ro as ClipByValue,Gl as Complex,oa as ComplexAbs,ls as Concat,Zo as Conv2D,Wl as Conv2DBackpropFilter,Jo as Conv2DBackpropInput,na as Conv3D,jl as Conv3DBackpropFilterV2,Ul as Conv3DBackpropInputV2,Qo as Cos,ei as Cosh,ti as CropAndResize,en as Cumsum,wx as CustomCallback,Za as DataStorage,Hl as DenseBincount,ri as DepthToSpace,tn as DepthwiseConv2dNative,ql as DepthwiseConv2dNativeBackpropFilter,Kl as DepthwiseConv2dNativeBackpropInput,Xl as Diag,sa as Dilation2D,Oc as Dilation2DBackpropFilter,Fc as Dilation2DBackpropInput,Ab as ENV,Lx as EarlyStopping,oi as Elu,Yl as EluGrad,zh as Environment,si as Equal,ni as Erf,on as Exp,us as ExpandDims,ii as Expm1,Zl as FFT,ia as Fill,ai as FlipLeftRight,nn as Floor,sn as FloorDiv,Pc as FromPixels,an as FusedBatchNorm,ks as FusedConv2D,_s as FusedDepthwiseConv2D,Pg as GPGPUContext,li as GatherNd,cs as GatherV2,ey as GraphModel,ui as Greater,ln as GreaterEqual,bx as History,Jl as IFFT,Fo as Identity,Ql as Imag,St as InputSpec,ci as IsFinite,pi as IsInf,mi as IsNan,js as KernelBackend,aa as LRN,tu as LRNGrad,Xf as LayerVariable,To as LayersModel,un as LeakyRelu,fi as Less,di as LessEqual,eu as LinSpace,cn as Log,hi as Log1p,Rb as LogSoftmax,gi as LogicalAnd,Ja as LogicalNot,Qa as LogicalOr,Hu as MathBackendCPU,Zu as MathBackendWebGL,pn as Max,fn as MaxPool,la as MaxPool3D,ou as MaxPool3DGrad,ru as MaxPoolGrad,nu as MaxPoolWithArgmax,mn as Maximum,dn as Mean,hn as Min,gn as Minimum,ua as MirrorPad,xi as Mod,ip as MomentumOptimizer,su as Multinomial,xn as Multiply,ps as Neg,bi as NonMaxSuppressionV3,wi as NonMaxSuppressionV4,ki as NonMaxSuppressionV5,yi as NotEqual,OI as OP_SCOPE_SUFFIX,yn as OneHot,ms as OnesLike,Pr as Optimizer,fs as Pack,bn as PadV2,$B as Pool,wn as Pow,kn as Prelu,_i as Prod,ap as RMSPropOptimizer,ho as RNN,ca as Range,Lb as Rank,iu as Real,rn as RealDiv,vi as Reciprocal,Gt as Reduction,_n as Relu,Cn as Relu6,ds as Reshape,vn as ResizeBilinear,lu as ResizeBilinearGrad,pa as ResizeNearestNeighbor,au as ResizeNearestNeighborGrad,In as Reverse,$i as RotateWithOffset,Nn as Round,Sn as Rsqrt,ul as SGDOptimizer,Ci as ScatterNd,hs as Select,Ii as Selu,qi as Sequential,An as Sigmoid,Si as Sign,Tn as Sin,Ni as Sinh,gs as Slice,$n as Softmax,Ti as Softplus,ma as SpaceToBatchND,uu as SparseToDense,xs as SplitV,En as Sqrt,fa as Square,Rn as SquaredDifference,Oo as Step,Ai as StridedSlice,Fn as Sub,Dn as Sum,Vr as SymbolicTensor,Ei as Tan,On as Tanh,Ve as Tensor,lt as TensorBuffer,ko as Tile,Di as TopK,cu as Transform,Pn as Transpose,pu as Unique,ys as Unpack,da as UnsortedSegmentSum,rl as Variable,bs as ZerosLike,ws as _FusedMatMul,It as abs,km as acos,_m as acosh,ee as add,fw as addN,bu as all,sl as any,il as argMax,vm as argMin,Cm as asin,Im as asinh,Nm as atan,Sm as atan2,Tm as atanh,wa as avgPool,Am as avgPool3d,mw as backend,N as backend_util,OG as basicLSTMCell,Ln as batchNorm,xw as batchNorm2d,yw as 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findBackendFactory,Ss as floor,yu as floorDiv,A_ as forceHalfFloat,Gn as fused,zn as gather,Qw as gatherND,Yh as gather_util,QV as getBackend,Bh as getGradient,Lc as getKernel,hm as getKernelsForBackend,jA as gpgpu_util,zW as grad,BW as grads,er as greater,io as greaterEqual,Mi as ifft,Nu as imag,$s as image,J4 as inTopKAsync,CC as initializers,Fx as input,Ir as io,Lu as irfft,Sw as isFinite,Tw as isInf,Aw as isNaN,Et as keep,Ar as kernel_impls,i0 as layers,Ca as leakyRelu,Su as less,Bo as lessEqual,ik as linalg,Ew as linspace,mz as loadGraphModel,kL as loadLayersModel,Mm as localResponseNormalization,lr as log,Tu as log1p,Dw as logSigmoid,Au as logSoftmax,zm as logSumExp,hr as logicalAnd,Ia as logicalNot,Eu as logicalOr,Ow as logicalXor,UU as losses,We as matMul,mN as math,ur as max,Na as maxPool,Bm as maxPool3d,Pw as maxPoolWithArgmax,Yr as maximum,dt as mean,Hc as memory,c0 as metrics,Pi as min,As as minimum,Vm as mirrorPad,Gm as mod,bL as model,p0 as models,Yc as moments,H4 as movingAverage,P as mul,hj as multiRNNCell,Mw as multinomial,He as neg,rf as nextFrame,Vu as norm,Vn as notEqual,Cs as oneHot,Nr as ones,tr as onesLike,S as op,wj as outerProduct,Fr as pad,vj as pad1d,Ij as pad2d,Sj as pad3d,Aj as pad4d,Lw as pool,Or as pow,Ta as prelu,rw as print,Du as prod,YV as profile,Lj as rand,Hj as randomGamma,lg as randomNormal,Es as randomUniform,Jc as range,JV as ready,ll as real,Wm as reciprocal,xu as registerBackend,_L as registerCallbackConstructor,Ob as registerGradient,el as registerKernel,PL as registerOp,m0 as regularizers,Sr as relu,Ru as relu6,eG as removeBackend,L as reshape,qt as reverse,t4 as reverse1d,o4 as reverse2d,s4 as reverse3d,a4 as reverse4d,Da as rfft,jm as round,Fu as rsqrt,le as scalar,Jw as scatterND,Zh as scatter_util,Ou as selu,Um as separableConv2d,wL as sequential,Q as serialization,AN as setBackend,oG as setPlatform,_9 as setWasmPath,v9 as setWasmPaths,Rk as setWebGLContext,Xw as setdiff1dAsync,yg as shared,qr as sigmoid,Hm as sign,jU as signal,Pu as sin,Mu as sinh,Re as slice,qm as slice1d,ug as slice2d,Km as slice3d,Qc as slice4d,sr as slice_util,Aa as softmax,Ts as softplus,Sa as spaceToBatchND,ef as sparseToDense,WU as spectral,cr as split,gt as sqrt,Oe as square,zu as squaredDifference,Co as squeeze,Bt as stack,Ds as step,Xm as stridedSlice,ce as sub,ge as sum,fu as sumOutType,Ym as tan,Oi as tanh,Rr as tensor,Vt as tensor1d,Li as tensor2d,iw as tensor3d,R4 as tensor4d,F4 as tensor5d,O4 as tensor6d,Mn as tensor_util,NN as test_util,V as tidy,zo as tile,ZV as time,Zm as topk,cl as train,Ue as transpose,Bu as truncatedNormal,ep as unique,FB as unregisterGradient,RB as unregisterKernel,Jm as unsortedSegmentSum,pr as unstack,dr as upcastType,y as util,VW as valueAndGrad,GW as valueAndGrads,Yw as variable,sg as variableGrads,gte as version,fz as version_converter,UV as version_core,yk as version_cpu,Gp as version_layers,cC as version_wasm,T_ as version_webgl,S5 as webgl,zA as webgl_util,Dt as where,Qm as whereAsync,ht as zeros,Ce as zerosLike};
 /**
  * @license
  * Copyright 2017 Google LLC. All Rights Reserved.
diff --git a/dist/tfjs.esm.js.map b/dist/tfjs.esm.js.map
index 6b2086e2..a49e54f9 100644
--- a/dist/tfjs.esm.js.map
+++ b/dist/tfjs.esm.js.map
@@ -1,7 +1,7 @@
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"../node_modules/@tensorflow/tfjs-data/src/sources/url_data_source.ts", "../node_modules/@tensorflow/tfjs-data/src/readers.ts", "../node_modules/@tensorflow/tfjs-data/src/version.ts", "../src/tfjs/tf-browser.ts"],
-  "sourcesContent": ["", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 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ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){err(\"requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];var contextAttributes={\"alpha\":!!GROWABLE_HEAP_I32()[a+(0>>2)],\"depth\":!!GROWABLE_HEAP_I32()[a+(4>>2)],\"stencil\":!!GROWABLE_HEAP_I32()[a+(8>>2)],\"antialias\":!!GROWABLE_HEAP_I32()[a+(12>>2)],\"premultipliedAlpha\":!!GROWABLE_HEAP_I32()[a+(16>>2)],\"preserveDrawingBuffer\":!!GROWABLE_HEAP_I32()[a+(20>>2)],\"powerPreference\":__emscripten_webgl_power_preferences[powerPreference],\"failIfMajorPerformanceCaveat\":!!GROWABLE_HEAP_I32()[a+(28>>2)],majorVersion:GROWABLE_HEAP_I32()[a+(32>>2)],minorVersion:GROWABLE_HEAP_I32()[a+(36>>2)],enableExtensionsByDefault:GROWABLE_HEAP_I32()[a+(40>>2)],explicitSwapControl:GROWABLE_HEAP_I32()[a+(44>>2)],proxyContextToMainThread:GROWABLE_HEAP_I32()[a+(48>>2)],renderViaOffscreenBackBuffer:GROWABLE_HEAP_I32()[a+(52>>2)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var 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\"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,HEAPU8,outPtr,maxBytesToWrite)}function writeArrayToMemory(array,buffer){HEAP8.set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;__ATINIT__.push({func:function(){___wasm_call_ctors()}});function preRun(){if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=HEAP32[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){}function _fd_write(fd,iov,iovcnt,pnum){var num=0;for(var i=0;i<iovcnt;i++){var ptr=HEAP32[iov+i*8>>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j])}num+=len}HEAP32[pnum>>2]=num;return 0}var asmLibraryArg={\"a\":_abort,\"d\":_emscripten_memcpy_big,\"e\":_emscripten_resize_heap,\"f\":_fd_close,\"c\":_fd_seek,\"b\":_fd_write};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"h\"]).apply(null,arguments)};var _init=Module[\"_init\"]=function(){return(_init=Module[\"_init\"]=Module[\"asm\"][\"i\"]).apply(null,arguments)};var _register_tensor=Module[\"_register_tensor\"]=function(){return(_register_tensor=Module[\"_register_tensor\"]=Module[\"asm\"][\"j\"]).apply(null,arguments)};var _dispose_data=Module[\"_dispose_data\"]=function(){return(_dispose_data=Module[\"_dispose_data\"]=Module[\"asm\"][\"k\"]).apply(null,arguments)};var _dispose=Module[\"_dispose\"]=function(){return(_dispose=Module[\"_dispose\"]=Module[\"asm\"][\"l\"]).apply(null,arguments)};var _Abs=Module[\"_Abs\"]=function(){return(_Abs=Module[\"_Abs\"]=Module[\"asm\"][\"n\"]).apply(null,arguments)};var _Add=Module[\"_Add\"]=function(){return(_Add=Module[\"_Add\"]=Module[\"asm\"][\"o\"]).apply(null,arguments)};var _AddN=Module[\"_AddN\"]=function(){return(_AddN=Module[\"_AddN\"]=Module[\"asm\"][\"p\"]).apply(null,arguments)};var _ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"q\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"r\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"s\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"t\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"u\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"v\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"w\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"x\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"y\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"z\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"B\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"C\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"D\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"E\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"F\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"G\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"H\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"I\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var 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_Rsqrt=Module[\"_Rsqrt\"]=function(){return(_Rsqrt=Module[\"_Rsqrt\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var _ScatterNd=Module[\"_ScatterNd\"]=function(){return(_ScatterNd=Module[\"_ScatterNd\"]=Module[\"asm\"][\"qa\"]).apply(null,arguments)};var _SelectV2=Module[\"_SelectV2\"]=function(){return(_SelectV2=Module[\"_SelectV2\"]=Module[\"asm\"][\"ra\"]).apply(null,arguments)};var _Sigmoid=Module[\"_Sigmoid\"]=function(){return(_Sigmoid=Module[\"_Sigmoid\"]=Module[\"asm\"][\"sa\"]).apply(null,arguments)};var _Sin=Module[\"_Sin\"]=function(){return(_Sin=Module[\"_Sin\"]=Module[\"asm\"][\"ta\"]).apply(null,arguments)};var _Softmax=Module[\"_Softmax\"]=function(){return(_Softmax=Module[\"_Softmax\"]=Module[\"asm\"][\"ua\"]).apply(null,arguments)};var _Sqrt=Module[\"_Sqrt\"]=function(){return(_Sqrt=Module[\"_Sqrt\"]=Module[\"asm\"][\"va\"]).apply(null,arguments)};var _Square=Module[\"_Square\"]=function(){return(_Square=Module[\"_Square\"]=Module[\"asm\"][\"wa\"]).apply(null,arguments)};var _SquaredDifference=Module[\"_SquaredDifference\"]=function(){return(_SquaredDifference=Module[\"_SquaredDifference\"]=Module[\"asm\"][\"xa\"]).apply(null,arguments)};var _Step=Module[\"_Step\"]=function(){return(_Step=Module[\"_Step\"]=Module[\"asm\"][\"ya\"]).apply(null,arguments)};var _StridedSlice=Module[\"_StridedSlice\"]=function(){return(_StridedSlice=Module[\"_StridedSlice\"]=Module[\"asm\"][\"za\"]).apply(null,arguments)};var _Sub=Module[\"_Sub\"]=function(){return(_Sub=Module[\"_Sub\"]=Module[\"asm\"][\"Aa\"]).apply(null,arguments)};var _Sum=Module[\"_Sum\"]=function(){return(_Sum=Module[\"_Sum\"]=Module[\"asm\"][\"Ba\"]).apply(null,arguments)};var _Tanh=Module[\"_Tanh\"]=function(){return(_Tanh=Module[\"_Tanh\"]=Module[\"asm\"][\"Ca\"]).apply(null,arguments)};var _Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(e){try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var 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+  "sourcesContent": ["", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n// \n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n// \n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = data.toString();\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "", "/*\nCopyright 2014 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\nvar global = this,\n    width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\nmath['seed' + rngname] = seedrandom;\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n}\n\n// End anonymous scope, and pass initial values.\n})(\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", "", "", "\nvar WasmBackendModuleThreadedSimd = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModuleThreadedSimd) {\n  WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};\n\nfunction GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAP32}function GROWABLE_HEAP_U32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPU32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer)}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!==\"undefined\"?WasmBackendModuleThreadedSimd:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var ENVIRONMENT_IS_PTHREAD=Module[\"ENVIRONMENT_IS_PTHREAD\"]||false;if(ENVIRONMENT_IS_PTHREAD){buffer=Module[\"buffer\"]}var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"};var nodeWorkerThreads;try{nodeWorkerThreads=require(\"worker_threads\")}catch(e){console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}global.Worker=nodeWorkerThreads.Worker}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(typeof _scriptDir !== \"undefined\" && _scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}if(ENVIRONMENT_IS_NODE){read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret}}else{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}if(ENVIRONMENT_IS_NODE){if(typeof performance===\"undefined\"){global.performance=require(\"perf_hooks\").performance}}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var Atomics_load=Atomics.load;var Atomics_store=Atomics.store;var Atomics_compareExchange=Atomics.compareExchange;var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str=\"\";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer)}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module[\"HEAP8\"]=HEAP8=new Int8Array(buf);Module[\"HEAP16\"]=HEAP16=new Int16Array(buf);Module[\"HEAP32\"]=HEAP32=new Int32Array(buf);Module[\"HEAPU8\"]=HEAPU8=new Uint8Array(buf);Module[\"HEAPU16\"]=HEAPU16=new Uint16Array(buf);Module[\"HEAPU32\"]=HEAPU32=new Uint32Array(buf);Module[\"HEAPF32\"]=HEAPF32=new Float32Array(buf);Module[\"HEAPF64\"]=HEAPF64=new Float64Array(buf)}var INITIAL_MEMORY=Module[\"INITIAL_MEMORY\"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module[\"wasmMemory\"];buffer=Module[\"buffer\"]}else{if(Module[\"wasmMemory\"]){wasmMemory=Module[\"wasmMemory\"]}else{wasmMemory=new WebAssembly.Memory({\"initial\":INITIAL_MEMORY/65536,\"maximum\":2147483648/65536,\"shared\":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){err(\"requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");if(ENVIRONMENT_IS_NODE){console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\")}throw Error(\"bad memory\")}}}if(wasmMemory){buffer=wasmMemory.buffer}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATEXIT__=[];var __ATPOSTRUN__=[];var runtimeInitialized=false;var runtimeExited=false;if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors()}});if(ENVIRONMENT_IS_PTHREAD)runtimeInitialized=true;function preRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"preRun\"]){if(typeof Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__)}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;runtimeExited=true}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){assert(!ENVIRONMENT_IS_PTHREAD,\"addRunDependency cannot be used in a pthread worker\");runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}if(ENVIRONMENT_IS_PTHREAD)console.error(\"Pthread aborting at \"+(new Error).stack);what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). Build with -s ASSERTIONS=1 for more info.\";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix=\"data:application/octet-stream;base64,\";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix=\"file://\";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile=\"tfjs-backend-wasm-threaded-simd.wasm\";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile)}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else{throw\"both async and sync fetching of the wasm failed\"}}catch(err){abort(err)}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch===\"function\"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmTable=Module[\"asm\"][\"F\"];wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency(\"wasm-instantiate\")})})}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency(\"wasm-instantiate\")}function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"],output[\"module\"])}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(receiver,function(reason){err(\"failed to asynchronously prepare wasm: \"+reason);abort(reason)})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming===\"function\"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch===\"function\"){return fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err(\"wasm streaming compile failed: \"+reason);err(\"falling back to ArrayBuffer instantiation\");return instantiateArrayBuffer(receiveInstantiatedSource)})})}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}if(Module[\"instantiateWasm\"]){try{var exports=Module[\"instantiateWasm\"](info,receiveInstance);return exports}catch(e){err(\"Module.instantiateWasm callback failed with error: \"+e);return false}}instantiateAsync().catch(readyPromiseReject);return{}}var ASM_CONSTS={8991:function($0,$1){setTimeout(function(){__emscripten_do_dispatch_to_thread($0,$1)},0)}};function initPthreadsJS(){PThread.initRuntime()}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return-28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw\"Atomics.notify returned an unexpected value \"+ret}Module[\"_emscripten_futex_wake\"]=_emscripten_futex_wake;function killThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! killThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in killThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined}function cancelThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cancelThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cancelThread!\";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({\"cmd\":\"cancel\"})}function cleanupThread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! cleanupThread() can only ever be called from main application thread!\";if(!pthread_ptr)throw\"Internal Error! Null pthread_ptr in cleanupThread!\";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker)}}var PThread={unusedWorkers:[],runningWorkers:[],initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker()}},initRuntime:function(){var tb=_malloc(228);for(var i=0;i<228/4;++i)GROWABLE_HEAP_U32()[tb/4+i]=0;GROWABLE_HEAP_I32()[tb+12>>2]=tb;var headPtr=tb+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=_malloc(512);for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),tb+100>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tb+40>>2,tb);__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(tb)},initWorker:function(){},pthreads:{},threadExitHandlers:[],setThreadStatus:function(){},runExitHandlers:function(){while(PThread.threadExitHandlers.length>0){PThread.threadExitHandlers.pop()()}if(ENVIRONMENT_IS_PTHREAD&&_pthread_self())___pthread_tsd_run_dtors()},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+56>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exit\"})}}},threadCancel:function(){PThread.runExitHandlers();var tb=_pthread_self();Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);_emscripten_futex_wake(tb+0,2147483647);__emscripten_thread_init(0,0,0);postMessage({\"cmd\":\"cancelDone\"})},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker)}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate()}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate()}PThread.runningWorkers=[]},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+100>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct)}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined})},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func()}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1}},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e[\"data\"];var cmd=d[\"cmd\"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d[\"targetThread\"]&&d[\"targetThread\"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d[\"transferList\"])}else{console.error('Internal error! Worker sent a message \"'+cmd+'\" to target pthread '+d[\"targetThread\"]+\", but that thread no longer exists!\")}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd===\"processQueuedMainThreadWork\"){_emscripten_main_thread_process_queued_calls()}else if(cmd===\"spawnThread\"){spawnThread(e.data)}else if(cmd===\"cleanupThread\"){cleanupThread(d[\"thread\"])}else if(cmd===\"killThread\"){killThread(d[\"thread\"])}else if(cmd===\"cancelThread\"){cancelThread(d[\"thread\"])}else if(cmd===\"loaded\"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread}}else if(cmd===\"print\"){out(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"printErr\"){err(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"alert\"){alert(\"Thread \"+d[\"threadId\"]+\": \"+d[\"text\"])}else if(cmd===\"exit\"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.threadInfoStruct+64>>2);if(detached){PThread.returnWorkerToPool(worker)}}else if(cmd===\"exitProcess\"){try{exit(d[\"returnCode\"])}catch(e){if(e instanceof ExitStatus)return;throw e}}else if(cmd===\"cancelDone\"){PThread.returnWorkerToPool(worker)}else if(cmd===\"objectTransfer\"){PThread.receiveObjectTransfer(e.data)}else if(e.data.target===\"setimmediate\"){worker.postMessage(e.data)}else{err(\"worker sent an unknown command \"+cmd)}PThread.currentProxiedOperationCallerThread=undefined};worker.onerror=function(e){err(\"pthread sent an error! \"+e.filename+\":\"+e.lineno+\": \"+e.message)};if(ENVIRONMENT_IS_NODE){worker.on(\"message\",function(data){worker.onmessage({data:data})});worker.on(\"error\",function(data){worker.onerror(data)});worker.on(\"exit\",function(data){})}worker.postMessage({\"cmd\":\"load\",\"urlOrBlob\":Module[\"mainScriptUrlOrBlob\"]||_scriptDir,\"wasmMemory\":wasmMemory,\"wasmModule\":wasmModule})},allocateUnusedWorker:function(){var pthreadMainJs=locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");PThread.unusedWorkers.push(new Worker(pthreadMainJs))},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0])}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop)}Module[\"establishStackSpace\"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module[\"getNoExitRuntime\"]=getNoExitRuntime;function invokeEntryPoint(ptr,arg){return wasmTable.get(ptr)(arg)}Module[\"invokeEntryPoint\"]=invokeEntryPoint;function ___assert_fail(condition,filename,line,func){abort(\"Assertion failed: \"+UTF8ToString(condition)+\", at: \"+[filename?UTF8ToString(filename):\"unknown filename\",line,func?UTF8ToString(func):\"unknown function\"])}function ___call_main(argc,argv){var returnCode=_main(argc,argv)}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process[\"hrtime\"]();return t[0]*1e3+t[1]/1e6}}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module[\"__performance_now_clock_drift\"]}}else if(typeof dateNow!==\"undefined\"){_emscripten_get_now=dateNow}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg)}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({\"cmd\":\"processQueuedMainThreadWork\"})}else if(ENVIRONMENT_IS_PTHREAD){postMessage({\"targetThread\":targetThreadId,\"cmd\":\"processThreadQueue\"})}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({\"cmd\":\"processThreadQueue\"})}return 1}function _abort(){abort()}function _emscripten_asm_const_int(code,sigPtr,argbuf){var args=readAsmConstArgs(sigPtr,argbuf);return ASM_CONSTS[code].apply(null,args)}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return-28;if(!ENVIRONMENT_IS_WEB){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret===\"timed-out\")return-73;if(ret===\"not-equal\")return-6;if(ret===\"ok\")return 0;throw\"Atomics.wait returned an unexpected value \"+ret}else{if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}var tNow=performance.now();var tEnd=tNow+timeout;var lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr);while(1){tNow=performance.now();if(tNow>tEnd){lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);return-73}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,0);if(lastAddr==0){break}_emscripten_main_thread_process_queued_calls();if(Atomics.load(GROWABLE_HEAP_I32(),addr>>2)!=val){return-6}lastAddr=Atomics.exchange(GROWABLE_HEAP_I32(),__emscripten_main_thread_futex>>2,addr)}return 0}}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num)}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return require(\"os\").cpus().length;return navigator[\"hardwareConcurrency\"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=arguments[2+i];GROWABLE_HEAP_F64()[b+i]=arg}var ret=_emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];var readAsmConstArgsArray=[];function readAsmConstArgs(sigPtr,buf){readAsmConstArgsArray.length=0;var ch;buf>>=2;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){var double=ch<105;if(double&&buf&1)buf++;readAsmConstArgsArray.push(double?GROWABLE_HEAP_F64()[buf++>>1]:GROWABLE_HEAP_I32()[buf]);++buf}return readAsmConstArgsArray}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i]}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();if(requestedSize<=oldSize){return false}var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i)}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[]},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){__ATEXIT__.push(JSEvents.removeAllEventListeners);JSEvents.removeEventListenersRegistered=true}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence})},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--)}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1)},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners()}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--)}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;__emscripten_call_on_thread(0,targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop)},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return\"\";if(target==window)return\"#window\";if(target==screen)return\"#screen\";return target&&target.nodeName?target.nodeName:\"\"},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas)}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;__emscripten_call_on_thread(0,targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop)}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):\"\";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height)}function maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!==\"undefined\"?document:0,typeof window!==\"undefined\"?window:0];function findEventTarget(target){target=maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!==\"undefined\"?document.querySelector(target):undefined);return domElement}function findCanvasEventTarget(target){return findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=findCanvasEventTarget(target);if(!canvas)return-4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height)}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return-4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension(\"ANGLE_instanced_arrays\");if(ext){ctx[\"vertexAttribDivisor\"]=function(index,divisor){ext[\"vertexAttribDivisorANGLE\"](index,divisor)};ctx[\"drawArraysInstanced\"]=function(mode,first,count,primcount){ext[\"drawArraysInstancedANGLE\"](mode,first,count,primcount)};ctx[\"drawElementsInstanced\"]=function(mode,count,type,indices,primcount){ext[\"drawElementsInstancedANGLE\"](mode,count,type,indices,primcount)};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension(\"OES_vertex_array_object\");if(ext){ctx[\"createVertexArray\"]=function(){return ext[\"createVertexArrayOES\"]()};ctx[\"deleteVertexArray\"]=function(vao){ext[\"deleteVertexArrayOES\"](vao)};ctx[\"bindVertexArray\"]=function(vao){ext[\"bindVertexArrayOES\"](vao)};ctx[\"isVertexArray\"]=function(vao){return ext[\"isVertexArrayOES\"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension(\"WEBGL_draw_buffers\");if(ext){ctx[\"drawBuffers\"]=function(n,bufs){ext[\"drawBuffersWEBGL\"](n,bufs)};return 1}}function __webgl_enable_WEBGL_multi_draw(ctx){return!!(ctx.multiDrawWebgl=ctx.getExtension(\"WEBGL_multi_draw\"))}var GL={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null}return ret},getSource:function(shader,count,string,length){var source=\"\";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len)}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext(\"webgl\",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault===\"undefined\"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context)}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return!(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents===\"object\")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension(\"EXT_disjoint_timer_query\");__webgl_enable_WEBGL_multi_draw(GLctx);var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(ext.indexOf(\"lose_context\")<0&&ext.indexOf(\"debug\")<0){GLctx.getExtension(ext)}})},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)==\"]\"){name=name.slice(0,name.lastIndexOf(\"[\"))}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+\"[\"+j+\"]\";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc}}}}};var __emscripten_webgl_power_preferences=[\"default\",\"low-power\",\"high-performance\"];function _emscripten_webgl_do_create_context(target,attributes){var a=attributes>>2;var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];var contextAttributes={\"alpha\":!!GROWABLE_HEAP_I32()[a+(0>>2)],\"depth\":!!GROWABLE_HEAP_I32()[a+(4>>2)],\"stencil\":!!GROWABLE_HEAP_I32()[a+(8>>2)],\"antialias\":!!GROWABLE_HEAP_I32()[a+(12>>2)],\"premultipliedAlpha\":!!GROWABLE_HEAP_I32()[a+(16>>2)],\"preserveDrawingBuffer\":!!GROWABLE_HEAP_I32()[a+(20>>2)],\"powerPreference\":__emscripten_webgl_power_preferences[powerPreference],\"failIfMajorPerformanceCaveat\":!!GROWABLE_HEAP_I32()[a+(28>>2)],majorVersion:GROWABLE_HEAP_I32()[a+(32>>2)],minorVersion:GROWABLE_HEAP_I32()[a+(36>>2)],enableExtensionsByDefault:GROWABLE_HEAP_I32()[a+(40>>2)],explicitSwapControl:GROWABLE_HEAP_I32()[a+(44>>2)],proxyContextToMainThread:GROWABLE_HEAP_I32()[a+(48>>2)],renderViaOffscreenBackBuffer:GROWABLE_HEAP_I32()[a+(52>>2)]};var canvas=findCanvasEventTarget(target);if(!canvas){return 0}if(contextAttributes.explicitSwapControl){return 0}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0}else{buffer.push(curr)}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=GROWABLE_HEAP_I32()[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j])}num+=len}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.threadExitHandlers.pop();if(execute)routine()}function _pthread_cleanup_push(routine,arg){PThread.threadExitHandlers.push(function(){wasmTable.get(routine)(arg)})}function spawnThread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw\"Internal Error! spawnThread() can only ever be called from main application thread!\";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw\"Internal error!\";if(!threadParams.pthread_ptr)throw\"Internal error, no pthread ptr!\";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(64>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(100>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(76>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(104+12>>2),threadParams.detached);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(172>>2),global_locale);worker.pthread=pthread;var msg={\"cmd\":\"run\",\"start_routine\":threadParams.startRoutine,\"arg\":threadParams.arg,\"threadInfoStruct\":threadParams.pthread_ptr,\"stackBase\":threadParams.stackBase,\"stackSize\":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList)};if(worker.loaded){worker.runPthread();delete worker.runPthread}}function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer===\"undefined\"){err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");return 6}if(!pthread_ptr){err(\"pthread_create called with a null thread pointer!\");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}if(error)return error;var stackSize=0;var stackBase=0;var detached=0;if(attr&&attr!=-1){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0}else{stackSize=2097152}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize)}else{stackBase-=stackSize;assert(stackBase>0)}var threadInfoStruct=_malloc(228);for(var i=0;i<228>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+152;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd=\"spawnThread\";postMessage(threadParams,transferList)}else{spawnThread(threadParams)}return 0}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:case 80:case 81:case 79:return-1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator===\"object\")return navigator[\"hardwareConcurrency\"]||1;return 1}}setErrNo(28);return-1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();var GLctx;var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={\"e\":___assert_fail,\"r\":___call_main,\"x\":__emscripten_notify_thread_queue,\"b\":_abort,\"y\":_emscripten_asm_const_int,\"j\":_emscripten_conditional_set_current_thread_status,\"c\":_emscripten_futex_wait,\"d\":_emscripten_futex_wake,\"f\":_emscripten_get_now,\"p\":_emscripten_memcpy_big,\"z\":_emscripten_num_logical_cores,\"u\":_emscripten_receive_on_main_thread_js,\"q\":_emscripten_resize_heap,\"v\":_emscripten_set_canvas_element_size,\"i\":_emscripten_set_current_thread_status,\"t\":_emscripten_set_thread_name,\"w\":_emscripten_webgl_create_context,\"m\":_fd_close,\"n\":_fd_seek,\"g\":_fd_write,\"o\":initPthreadsJS,\"a\":wasmMemory||Module[\"wasmMemory\"],\"k\":_pthread_cleanup_pop,\"l\":_pthread_cleanup_push,\"h\":_pthread_create,\"s\":_sysconf};var asm=createWasm();var ___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=function(){return(___wasm_call_ctors=Module[\"___wasm_call_ctors\"]=Module[\"asm\"][\"A\"]).apply(null,arguments)};var 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_ArgMax=Module[\"_ArgMax\"]=function(){return(_ArgMax=Module[\"_ArgMax\"]=Module[\"asm\"][\"J\"]).apply(null,arguments)};var _AvgPool=Module[\"_AvgPool\"]=function(){return(_AvgPool=Module[\"_AvgPool\"]=Module[\"asm\"][\"K\"]).apply(null,arguments)};var _BatchMatMul=Module[\"_BatchMatMul\"]=function(){return(_BatchMatMul=Module[\"_BatchMatMul\"]=Module[\"asm\"][\"L\"]).apply(null,arguments)};var _Ceil=Module[\"_Ceil\"]=function(){return(_Ceil=Module[\"_Ceil\"]=Module[\"asm\"][\"M\"]).apply(null,arguments)};var _ClipByValue=Module[\"_ClipByValue\"]=function(){return(_ClipByValue=Module[\"_ClipByValue\"]=Module[\"asm\"][\"N\"]).apply(null,arguments)};var _Conv2D=Module[\"_Conv2D\"]=function(){return(_Conv2D=Module[\"_Conv2D\"]=Module[\"asm\"][\"O\"]).apply(null,arguments)};var _Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=function(){return(_Conv2DBackpropInput=Module[\"_Conv2DBackpropInput\"]=Module[\"asm\"][\"P\"]).apply(null,arguments)};var _Cos=Module[\"_Cos\"]=function(){return(_Cos=Module[\"_Cos\"]=Module[\"asm\"][\"Q\"]).apply(null,arguments)};var _CropAndResize=Module[\"_CropAndResize\"]=function(){return(_CropAndResize=Module[\"_CropAndResize\"]=Module[\"asm\"][\"R\"]).apply(null,arguments)};var _Cumsum=Module[\"_Cumsum\"]=function(){return(_Cumsum=Module[\"_Cumsum\"]=Module[\"asm\"][\"S\"]).apply(null,arguments)};var _DepthToSpace=Module[\"_DepthToSpace\"]=function(){return(_DepthToSpace=Module[\"_DepthToSpace\"]=Module[\"asm\"][\"T\"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=function(){return(_DepthwiseConv2dNative=Module[\"_DepthwiseConv2dNative\"]=Module[\"asm\"][\"U\"]).apply(null,arguments)};var _Equal=Module[\"_Equal\"]=function(){return(_Equal=Module[\"_Equal\"]=Module[\"asm\"][\"V\"]).apply(null,arguments)};var _Exp=Module[\"_Exp\"]=function(){return(_Exp=Module[\"_Exp\"]=Module[\"asm\"][\"W\"]).apply(null,arguments)};var _FlipLeftRight=Module[\"_FlipLeftRight\"]=function(){return(_FlipLeftRight=Module[\"_FlipLeftRight\"]=Module[\"asm\"][\"X\"]).apply(null,arguments)};var _Floor=Module[\"_Floor\"]=function(){return(_Floor=Module[\"_Floor\"]=Module[\"asm\"][\"Y\"]).apply(null,arguments)};var _FloorDiv=Module[\"_FloorDiv\"]=function(){return(_FloorDiv=Module[\"_FloorDiv\"]=Module[\"asm\"][\"Z\"]).apply(null,arguments)};var _FusedBatchNorm=Module[\"_FusedBatchNorm\"]=function(){return(_FusedBatchNorm=Module[\"_FusedBatchNorm\"]=Module[\"asm\"][\"_\"]).apply(null,arguments)};var _FusedConv2D=Module[\"_FusedConv2D\"]=function(){return(_FusedConv2D=Module[\"_FusedConv2D\"]=Module[\"asm\"][\"$\"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=function(){return(_FusedDepthwiseConv2D=Module[\"_FusedDepthwiseConv2D\"]=Module[\"asm\"][\"aa\"]).apply(null,arguments)};var _Gather=Module[\"_Gather\"]=function(){return(_Gather=Module[\"_Gather\"]=Module[\"asm\"][\"ba\"]).apply(null,arguments)};var _GatherNd=Module[\"_GatherNd\"]=function(){return(_GatherNd=Module[\"_GatherNd\"]=Module[\"asm\"][\"ca\"]).apply(null,arguments)};var _Greater=Module[\"_Greater\"]=function(){return(_Greater=Module[\"_Greater\"]=Module[\"asm\"][\"da\"]).apply(null,arguments)};var _GreaterEqual=Module[\"_GreaterEqual\"]=function(){return(_GreaterEqual=Module[\"_GreaterEqual\"]=Module[\"asm\"][\"ea\"]).apply(null,arguments)};var _LeakyRelu=Module[\"_LeakyRelu\"]=function(){return(_LeakyRelu=Module[\"_LeakyRelu\"]=Module[\"asm\"][\"fa\"]).apply(null,arguments)};var _Less=Module[\"_Less\"]=function(){return(_Less=Module[\"_Less\"]=Module[\"asm\"][\"ga\"]).apply(null,arguments)};var _LessEqual=Module[\"_LessEqual\"]=function(){return(_LessEqual=Module[\"_LessEqual\"]=Module[\"asm\"][\"ha\"]).apply(null,arguments)};var _Log=Module[\"_Log\"]=function(){return(_Log=Module[\"_Log\"]=Module[\"asm\"][\"ia\"]).apply(null,arguments)};var _LogicalAnd=Module[\"_LogicalAnd\"]=function(){return(_LogicalAnd=Module[\"_LogicalAnd\"]=Module[\"asm\"][\"ja\"]).apply(null,arguments)};var _Max=Module[\"_Max\"]=function(){return(_Max=Module[\"_Max\"]=Module[\"asm\"][\"ka\"]).apply(null,arguments)};var _MaxPool=Module[\"_MaxPool\"]=function(){return(_MaxPool=Module[\"_MaxPool\"]=Module[\"asm\"][\"la\"]).apply(null,arguments)};var _Maximum=Module[\"_Maximum\"]=function(){return(_Maximum=Module[\"_Maximum\"]=Module[\"asm\"][\"ma\"]).apply(null,arguments)};var _Mean=Module[\"_Mean\"]=function(){return(_Mean=Module[\"_Mean\"]=Module[\"asm\"][\"na\"]).apply(null,arguments)};var _Min=Module[\"_Min\"]=function(){return(_Min=Module[\"_Min\"]=Module[\"asm\"][\"oa\"]).apply(null,arguments)};var _Minimum=Module[\"_Minimum\"]=function(){return(_Minimum=Module[\"_Minimum\"]=Module[\"asm\"][\"pa\"]).apply(null,arguments)};var 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_OneHot=Module[\"_OneHot\"]=function(){return(_OneHot=Module[\"_OneHot\"]=Module[\"asm\"][\"wa\"]).apply(null,arguments)};var _PadV2=Module[\"_PadV2\"]=function(){return(_PadV2=Module[\"_PadV2\"]=Module[\"asm\"][\"xa\"]).apply(null,arguments)};var _Pow=Module[\"_Pow\"]=function(){return(_Pow=Module[\"_Pow\"]=Module[\"asm\"][\"ya\"]).apply(null,arguments)};var _Prelu=Module[\"_Prelu\"]=function(){return(_Prelu=Module[\"_Prelu\"]=Module[\"asm\"][\"za\"]).apply(null,arguments)};var _Prod=Module[\"_Prod\"]=function(){return(_Prod=Module[\"_Prod\"]=Module[\"asm\"][\"Aa\"]).apply(null,arguments)};var _RealDiv=Module[\"_RealDiv\"]=function(){return(_RealDiv=Module[\"_RealDiv\"]=Module[\"asm\"][\"Ba\"]).apply(null,arguments)};var _Relu=Module[\"_Relu\"]=function(){return(_Relu=Module[\"_Relu\"]=Module[\"asm\"][\"Ca\"]).apply(null,arguments)};var _Relu6=Module[\"_Relu6\"]=function(){return(_Relu6=Module[\"_Relu6\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var 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___pthread_tsd_run_dtors=Module[\"___pthread_tsd_run_dtors\"]=function(){return(___pthread_tsd_run_dtors=Module[\"___pthread_tsd_run_dtors\"]=Module[\"asm\"][\"db\"]).apply(null,arguments)};var _emscripten_main_thread_process_queued_calls=Module[\"_emscripten_main_thread_process_queued_calls\"]=function(){return(_emscripten_main_thread_process_queued_calls=Module[\"_emscripten_main_thread_process_queued_calls\"]=Module[\"asm\"][\"eb\"]).apply(null,arguments)};var _emscripten_current_thread_process_queued_calls=Module[\"_emscripten_current_thread_process_queued_calls\"]=function(){return(_emscripten_current_thread_process_queued_calls=Module[\"_emscripten_current_thread_process_queued_calls\"]=Module[\"asm\"][\"fb\"]).apply(null,arguments)};var _emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=function(){return(_emscripten_register_main_browser_thread_id=Module[\"_emscripten_register_main_browser_thread_id\"]=Module[\"asm\"][\"gb\"]).apply(null,arguments)};var __emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=function(){return(__emscripten_do_dispatch_to_thread=Module[\"__emscripten_do_dispatch_to_thread\"]=Module[\"asm\"][\"hb\"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=function(){return(_emscripten_sync_run_in_main_thread_4=Module[\"_emscripten_sync_run_in_main_thread_4\"]=Module[\"asm\"][\"ib\"]).apply(null,arguments)};var _emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=function(){return(_emscripten_run_in_main_runtime_thread_js=Module[\"_emscripten_run_in_main_runtime_thread_js\"]=Module[\"asm\"][\"jb\"]).apply(null,arguments)};var __emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=function(){return(__emscripten_call_on_thread=Module[\"__emscripten_call_on_thread\"]=Module[\"asm\"][\"kb\"]).apply(null,arguments)};var _emscripten_tls_init=Module[\"_emscripten_tls_init\"]=function(){return(_emscripten_tls_init=Module[\"_emscripten_tls_init\"]=Module[\"asm\"][\"lb\"]).apply(null,arguments)};var __emscripten_thread_init=Module[\"__emscripten_thread_init\"]=function(){return(__emscripten_thread_init=Module[\"__emscripten_thread_init\"]=Module[\"asm\"][\"mb\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"nb\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"ob\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"pb\"]).apply(null,arguments)};var _emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=function(){return(_emscripten_stack_set_limits=Module[\"_emscripten_stack_set_limits\"]=Module[\"asm\"][\"qb\"]).apply(null,arguments)};var _memalign=Module[\"_memalign\"]=function(){return(_memalign=Module[\"_memalign\"]=Module[\"asm\"][\"rb\"]).apply(null,arguments)};var __emscripten_allow_main_runtime_queued_calls=Module[\"__emscripten_allow_main_runtime_queued_calls\"]=9880;var __emscripten_main_thread_futex=Module[\"__emscripten_main_thread_futex\"]=11368;Module[\"cwrap\"]=cwrap;Module[\"PThread\"]=PThread;Module[\"PThread\"]=PThread;Module[\"wasmMemory\"]=wasmMemory;Module[\"ExitStatus\"]=ExitStatus;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}if(ENVIRONMENT_IS_PTHREAD){readyPromiseResolve(Module);postMessage({\"cmd\":\"loaded\"});return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;function exit(status,implicit){if(implicit&&noExitRuntime&&status===0){return}if(!implicit){if(ENVIRONMENT_IS_PTHREAD){postMessage({\"cmd\":\"exitProcess\",\"returnCode\":status});throw new ExitStatus(status)}else{}}if(noExitRuntime){}else{PThread.terminateAllThreads();EXITSTATUS=status;exitRuntime();if(Module[\"onExit\"])Module[\"onExit\"](status);ABORT=true}quit_(status,new ExitStatus(status))}if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}if(ENVIRONMENT_IS_PTHREAD){noExitRuntime=false;PThread.initWorker()}run();\n\n\n  return WasmBackendModuleThreadedSimd.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModuleThreadedSimd;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModuleThreadedSimd; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd;\n", "\nvar WasmBackendModule = (function() {\n  var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;\n  if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;\n  return (\nfunction(WasmBackendModule) {\n  WasmBackendModule = WasmBackendModule || {};\n\nvar Module=typeof WasmBackendModule!==\"undefined\"?WasmBackendModule:{};var readyPromiseResolve,readyPromiseReject;Module[\"ready\"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject});var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key]}}var arguments_=[];var thisProgram=\"./this.program\";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window===\"object\";ENVIRONMENT_IS_WORKER=typeof importScripts===\"function\";ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var scriptDirectory=\"\";function locateFile(path){if(Module[\"locateFile\"]){return Module[\"locateFile\"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary,setWindowTitle;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=require(\"path\").dirname(scriptDirectory)+\"/\"}else{scriptDirectory=__dirname+\"/\"}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=require(\"fs\");if(!nodePath)nodePath=require(\"path\");filename=nodePath[\"normalize\"](filename);return nodeFS[\"readFileSync\"](filename,binary?null:\"utf8\")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret)}assert(ret.buffer);return ret};if(process[\"argv\"].length>1){thisProgram=process[\"argv\"][1].replace(/\\\\/g,\"/\")}arguments_=process[\"argv\"].slice(2);process[\"on\"](\"uncaughtException\",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process[\"on\"](\"unhandledRejection\",abort);quit_=function(status){process[\"exit\"](status)};Module[\"inspect\"]=function(){return\"[Emscripten Module object]\"}}else if(ENVIRONMENT_IS_SHELL){if(typeof read!=\"undefined\"){read_=function shell_read(f){return read(f)}}readBinary=function readBinary(f){var data;if(typeof readbuffer===\"function\"){return new Uint8Array(readbuffer(f))}data=read(f,\"binary\");assert(typeof data===\"object\");return data};if(typeof scriptArgs!=\"undefined\"){arguments_=scriptArgs}else if(typeof arguments!=\"undefined\"){arguments_=arguments}if(typeof quit===\"function\"){quit_=function(status){quit(status)}}if(typeof print!==\"undefined\"){if(typeof console===\"undefined\")console={};console.log=print;console.warn=console.error=typeof printErr!==\"undefined\"?printErr:print}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href}else if(typeof document!==\"undefined\"&&document.currentScript){scriptDirectory=document.currentScript.src}if(_scriptDir){scriptDirectory=_scriptDir}if(scriptDirectory.indexOf(\"blob:\")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf(\"/\")+1)}else{scriptDirectory=\"\"}{read_=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function(url){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,false);xhr.responseType=\"arraybuffer\";xhr.send(null);return new Uint8Array(xhr.response)}}readAsync=function(url,onload,onerror){var xhr=new XMLHttpRequest;xhr.open(\"GET\",url,true);xhr.responseType=\"arraybuffer\";xhr.onload=function(){if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror()};xhr.onerror=onerror;xhr.send(null)}}setWindowTitle=function(title){document.title=title}}else{}var out=Module[\"print\"]||console.log.bind(console);var err=Module[\"printErr\"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key]}}moduleOverrides=null;if(Module[\"arguments\"])arguments_=Module[\"arguments\"];if(Module[\"thisProgram\"])thisProgram=Module[\"thisProgram\"];if(Module[\"quit\"])quit_=Module[\"quit\"];var wasmBinary;if(Module[\"wasmBinary\"])wasmBinary=Module[\"wasmBinary\"];var noExitRuntime=Module[\"noExitRuntime\"]||true;if(typeof WebAssembly!==\"object\"){abort(\"no native wasm support detected\")}var wasmMemory;var ABORT=false;var EXITSTATUS;function assert(condition,text){if(!condition){abort(\"Assertion failed: \"+text)}}function getCFunc(ident){var func=Module[\"_\"+ident];assert(func,\"Cannot call unknown function \"+ident+\", make sure it is exported\");return func}function ccall(ident,returnType,argTypes,args,opts){var toC={\"string\":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len)}return ret},\"array\":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType===\"string\")return UTF8ToString(ret);if(returnType===\"boolean\")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i])}else{cArgs[i]=args[i]}}}var ret=func.apply(null,cArgs);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type===\"number\"});var numericRet=returnType!==\"string\";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments,opts)}}var UTF8Decoder=typeof TextDecoder!==\"undefined\"?new TextDecoder(\"utf8\"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else{var str=\"\";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63}if(u0<65536){str+=String.fromCharCode(u0)}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023)}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):\"\"}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return 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Module[\"preRun\"]==\"function\")Module[\"preRun\"]=[Module[\"preRun\"]];while(Module[\"preRun\"].length){addOnPreRun(Module[\"preRun\"].shift())}}callRuntimeCallbacks(__ATPRERUN__)}function initRuntime(){runtimeInitialized=true;callRuntimeCallbacks(__ATINIT__)}function preMain(){callRuntimeCallbacks(__ATMAIN__)}function postRun(){if(Module[\"postRun\"]){if(typeof Module[\"postRun\"]==\"function\")Module[\"postRun\"]=[Module[\"postRun\"]];while(Module[\"postRun\"].length){addOnPostRun(Module[\"postRun\"].shift())}}callRuntimeCallbacks(__ATPOSTRUN__)}function addOnPreRun(cb){__ATPRERUN__.unshift(cb)}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb)}var runDependencies=0;var runDependencyWatcher=null;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}}function removeRunDependency(id){runDependencies--;if(Module[\"monitorRunDependencies\"]){Module[\"monitorRunDependencies\"](runDependencies)}if(runDependencies==0){if(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback()}}}Module[\"preloadedImages\"]={};Module[\"preloadedAudios\"]={};function abort(what){if(Module[\"onAbort\"]){Module[\"onAbort\"](what)}what+=\"\";err(what);ABORT=true;EXITSTATUS=1;what=\"abort(\"+what+\"). 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fetch(wasmBinaryFile,{credentials:\"same-origin\"}).then(function(response){if(!response[\"ok\"]){throw\"failed to load wasm binary file at '\"+wasmBinaryFile+\"'\"}return response[\"arrayBuffer\"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else{if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response))},reject)})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={\"a\":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module[\"asm\"]=exports;wasmMemory=Module[\"asm\"][\"g\"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module[\"asm\"][\"m\"];removeRunDependency(\"wasm-instantiate\")}addRunDependency(\"wasm-instantiate\");function receiveInstantiatedSource(output){receiveInstance(output[\"instance\"])}function instantiateArrayBuffer(receiver){return 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false}}instantiateAsync().catch(readyPromiseReject);return{}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback==\"function\"){callback(Module);continue}var func=callback.func;if(typeof func===\"number\"){if(callback.arg===undefined){wasmTable.get(func)()}else{wasmTable.get(func)(callback.arg)}}else{func(callback.arg===undefined?null:callback.arg)}}}function _abort(){abort()}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num)}function _emscripten_get_heap_size(){return HEAPU8.length}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=_emscripten_get_heap_size();var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var 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_Tile=Module[\"_Tile\"]=function(){return(_Tile=Module[\"_Tile\"]=Module[\"asm\"][\"Da\"]).apply(null,arguments)};var _TopK=Module[\"_TopK\"]=function(){return(_TopK=Module[\"_TopK\"]=Module[\"asm\"][\"Ea\"]).apply(null,arguments)};var _Transpose=Module[\"_Transpose\"]=function(){return(_Transpose=Module[\"_Transpose\"]=Module[\"asm\"][\"Fa\"]).apply(null,arguments)};var __FusedMatMul=Module[\"__FusedMatMul\"]=function(){return(__FusedMatMul=Module[\"__FusedMatMul\"]=Module[\"asm\"][\"Ga\"]).apply(null,arguments)};var _malloc=Module[\"_malloc\"]=function(){return(_malloc=Module[\"_malloc\"]=Module[\"asm\"][\"Ha\"]).apply(null,arguments)};var _free=Module[\"_free\"]=function(){return(_free=Module[\"_free\"]=Module[\"asm\"][\"Ia\"]).apply(null,arguments)};var stackSave=Module[\"stackSave\"]=function(){return(stackSave=Module[\"stackSave\"]=Module[\"asm\"][\"Ja\"]).apply(null,arguments)};var stackRestore=Module[\"stackRestore\"]=function(){return(stackRestore=Module[\"stackRestore\"]=Module[\"asm\"][\"Ka\"]).apply(null,arguments)};var stackAlloc=Module[\"stackAlloc\"]=function(){return(stackAlloc=Module[\"stackAlloc\"]=Module[\"asm\"][\"La\"]).apply(null,arguments)};Module[\"cwrap\"]=cwrap;var calledRun;function ExitStatus(status){this.name=\"ExitStatus\";this.message=\"Program terminated with exit(\"+status+\")\";this.status=status}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller};function run(args){args=args||arguments_;if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module[\"calledRun\"]=true;if(ABORT)return;initRuntime();preMain();readyPromiseResolve(Module);if(Module[\"onRuntimeInitialized\"])Module[\"onRuntimeInitialized\"]();postRun()}if(Module[\"setStatus\"]){Module[\"setStatus\"](\"Running...\");setTimeout(function(){setTimeout(function(){Module[\"setStatus\"](\"\")},1);doRun()},1)}else{doRun()}}Module[\"run\"]=run;if(Module[\"preInit\"]){if(typeof Module[\"preInit\"]==\"function\")Module[\"preInit\"]=[Module[\"preInit\"]];while(Module[\"preInit\"].length>0){Module[\"preInit\"].pop()()}}run();\n\n\n  return WasmBackendModule.ready\n}\n);\n})();\nif (typeof exports === 'object' && typeof module === 'object')\n  module.exports = WasmBackendModule;\nelse if (typeof define === 'function' && define['amd'])\n  define([], function() { return WasmBackendModule; });\nelse if (typeof exports === 'object')\n  exports[\"WasmBackendModule\"] = WasmBackendModule;\n", "// A port of an algorithm by Johannes Baag\u00F8e <baagoe@baagoe.com>, 2010\n// http://baagoe.com/en/RandomMusings/javascript/\n// https://github.com/nquinlan/better-random-numbers-for-javascript-mirror\n// Original work is under MIT license -\n\n// Copyright (C) 2010 by Johannes Baag\u00F8e <baagoe@baagoe.org>\n//\n// Permission is hereby granted, free of charge, to any person obtaining a copy\n// of this software and associated documentation files (the \"Software\"), to deal\n// in the Software without restriction, including without limitation the rights\n// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n// copies of the Software, and to permit persons to whom the Software is\n// furnished to do so, subject to the following conditions:\n//\n// The above copyright notice and this permission notice shall be included in\n// all copies or substantial portions of the Software.\n//\n// THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n// THE SOFTWARE.\n\n\n\n(function(global, module, define) {\n\nfunction Alea(seed) {\n  var me = this, mash = Mash();\n\n  me.next = function() {\n    var t = 2091639 * me.s0 + me.c * 2.3283064365386963e-10; // 2^-32\n    me.s0 = me.s1;\n    me.s1 = me.s2;\n    return me.s2 = t - (me.c = t | 0);\n  };\n\n  // Apply the seeding algorithm from Baagoe.\n  me.c = 1;\n  me.s0 = mash(' ');\n  me.s1 = mash(' ');\n  me.s2 = mash(' ');\n  me.s0 -= mash(seed);\n  if (me.s0 < 0) { me.s0 += 1; }\n  me.s1 -= mash(seed);\n  if (me.s1 < 0) { me.s1 += 1; }\n  me.s2 -= mash(seed);\n  if (me.s2 < 0) { me.s2 += 1; }\n  mash = null;\n}\n\nfunction copy(f, t) {\n  t.c = f.c;\n  t.s0 = f.s0;\n  t.s1 = f.s1;\n  t.s2 = f.s2;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new Alea(seed),\n      state = opts && opts.state,\n      prng = xg.next;\n  prng.int32 = function() { return (xg.next() * 0x100000000) | 0; }\n  prng.double = function() {\n    return prng() + (prng() * 0x200000 | 0) * 1.1102230246251565e-16; // 2^-53\n  };\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nfunction Mash() {\n  var n = 0xefc8249d;\n\n  var mash = function(data) {\n    data = String(data);\n    for (var i = 0; i < data.length; i++) {\n      n += data.charCodeAt(i);\n      var h = 0.02519603282416938 * n;\n      n = h >>> 0;\n      h -= n;\n      h *= n;\n      n = h >>> 0;\n      h -= n;\n      n += h * 0x100000000; // 2^32\n    }\n    return (n >>> 0) * 2.3283064365386963e-10; // 2^-32\n  };\n\n  return mash;\n}\n\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.alea = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xor128\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n\n  // Set up generator function.\n  me.next = function() {\n    var t = me.x ^ (me.x << 11);\n    me.x = me.y;\n    me.y = me.z;\n    me.z = me.w;\n    return me.w ^= (me.w >>> 19) ^ t ^ (t >>> 8);\n  };\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor128 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorwow\" prng algorithm by\n// George Marsaglia.  See http://www.jstatsoft.org/v08/i14/paper\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var t = (me.x ^ (me.x >>> 2));\n    me.x = me.y; me.y = me.z; me.z = me.w; me.w = me.v;\n    return (me.d = (me.d + 362437 | 0)) +\n       (me.v = (me.v ^ (me.v << 4)) ^ (t ^ (t << 1))) | 0;\n  };\n\n  me.x = 0;\n  me.y = 0;\n  me.z = 0;\n  me.w = 0;\n  me.v = 0;\n\n  if (seed === (seed | 0)) {\n    // Integer seed.\n    me.x = seed;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 64; k++) {\n    me.x ^= strseed.charCodeAt(k) | 0;\n    if (k == strseed.length) {\n      me.d = me.x << 10 ^ me.x >>> 4;\n    }\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.x = f.x;\n  t.y = f.y;\n  t.z = f.z;\n  t.w = f.w;\n  t.v = f.v;\n  t.d = f.d;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorwow = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "// A Javascript implementaion of the \"xorshift7\" algorithm by\n// Fran\u00E7ois Panneton and Pierre L'ecuyer:\n// \"On the Xorgshift Random Number Generators\"\n// http://saluc.engr.uconn.edu/refs/crypto/rng/panneton05onthexorshift.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    // Update xor generator.\n    var X = me.x, i = me.i, t, v, w;\n    t = X[i]; t ^= (t >>> 7); v = t ^ (t << 24);\n    t = X[(i + 1) & 7]; v ^= t ^ (t >>> 10);\n    t = X[(i + 3) & 7]; v ^= t ^ (t >>> 3);\n    t = X[(i + 4) & 7]; v ^= t ^ (t << 7);\n    t = X[(i + 7) & 7]; t = t ^ (t << 13); v ^= t ^ (t << 9);\n    X[i] = v;\n    me.i = (i + 1) & 7;\n    return v;\n  };\n\n  function init(me, seed) {\n    var j, w, X = [];\n\n    if (seed === (seed | 0)) {\n      // Seed state array using a 32-bit integer.\n      w = X[0] = seed;\n    } else {\n      // Seed state using a string.\n      seed = '' + seed;\n      for (j = 0; j < seed.length; ++j) {\n        X[j & 7] = (X[j & 7] << 15) ^\n            (seed.charCodeAt(j) + X[(j + 1) & 7] << 13);\n      }\n    }\n    // Enforce an array length of 8, not all zeroes.\n    while (X.length < 8) X.push(0);\n    for (j = 0; j < 8 && X[j] === 0; ++j);\n    if (j == 8) w = X[7] = -1; else w = X[j];\n\n    me.x = X;\n    me.i = 0;\n\n    // Discard an initial 256 values.\n    for (j = 256; j > 0; --j) {\n      me.next();\n    }\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.x = f.x.slice();\n  t.i = f.i;\n  return t;\n}\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.x) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xorshift7 = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n", "// A Javascript implementaion of Richard Brent's Xorgens xor4096 algorithm.\n//\n// This fast non-cryptographic random number generator is designed for\n// use in Monte-Carlo algorithms. It combines a long-period xorshift\n// generator with a Weyl generator, and it passes all common batteries\n// of stasticial tests for randomness while consuming only a few nanoseconds\n// for each prng generated.  For background on the generator, see Brent's\n// paper: \"Some long-period random number generators using shifts and xors.\"\n// http://arxiv.org/pdf/1004.3115v1.pdf\n//\n// Usage:\n//\n// var xor4096 = require('xor4096');\n// random = xor4096(1);                        // Seed with int32 or string.\n// assert.equal(random(), 0.1520436450538547); // (0, 1) range, 53 bits.\n// assert.equal(random.int32(), 1806534897);   // signed int32, 32 bits.\n//\n// For nonzero numeric keys, this impelementation provides a sequence\n// identical to that by Brent's xorgens 3 implementaion in C.  This\n// implementation also provides for initalizing the generator with\n// string seeds, or for saving and restoring the state of the generator.\n//\n// On Chrome, this prng benchmarks about 2.1 times slower than\n// Javascript's built-in Math.random().\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this;\n\n  // Set up generator function.\n  me.next = function() {\n    var w = me.w,\n        X = me.X, i = me.i, t, v;\n    // Update Weyl generator.\n    me.w = w = (w + 0x61c88647) | 0;\n    // Update xor generator.\n    v = X[(i + 34) & 127];\n    t = X[i = ((i + 1) & 127)];\n    v ^= v << 13;\n    t ^= t << 17;\n    v ^= v >>> 15;\n    t ^= t >>> 12;\n    // Update Xor generator array state.\n    v = X[i] = v ^ t;\n    me.i = i;\n    // Result is the combination.\n    return (v + (w ^ (w >>> 16))) | 0;\n  };\n\n  function init(me, seed) {\n    var t, v, i, j, w, X = [], limit = 128;\n    if (seed === (seed | 0)) {\n      // Numeric seeds initialize v, which is used to generates X.\n      v = seed;\n      seed = null;\n    } else {\n      // String seeds are mixed into v and X one character at a time.\n      seed = seed + '\\0';\n      v = 0;\n      limit = Math.max(limit, seed.length);\n    }\n    // Initialize circular array and weyl value.\n    for (i = 0, j = -32; j < limit; ++j) {\n      // Put the unicode characters into the array, and shuffle them.\n      if (seed) v ^= seed.charCodeAt((j + 32) % seed.length);\n      // After 32 shuffles, take v as the starting w value.\n      if (j === 0) w = v;\n      v ^= v << 10;\n      v ^= v >>> 15;\n      v ^= v << 4;\n      v ^= v >>> 13;\n      if (j >= 0) {\n        w = (w + 0x61c88647) | 0;     // Weyl.\n        t = (X[j & 127] ^= (v + w));  // Combine xor and weyl to init array.\n        i = (0 == t) ? i + 1 : 0;     // Count zeroes.\n      }\n    }\n    // We have detected all zeroes; make the key nonzero.\n    if (i >= 128) {\n      X[(seed && seed.length || 0) & 127] = -1;\n    }\n    // Run the generator 512 times to further mix the state before using it.\n    // Factoring this as a function slows the main generator, so it is just\n    // unrolled here.  The weyl generator is not advanced while warming up.\n    i = 127;\n    for (j = 4 * 128; j > 0; --j) {\n      v = X[(i + 34) & 127];\n      t = X[i = ((i + 1) & 127)];\n      v ^= v << 13;\n      t ^= t << 17;\n      v ^= v >>> 15;\n      t ^= t >>> 12;\n      X[i] = v ^ t;\n    }\n    // Storing state as object members is faster than using closure variables.\n    me.w = w;\n    me.X = X;\n    me.i = i;\n  }\n\n  init(me, seed);\n}\n\nfunction copy(f, t) {\n  t.i = f.i;\n  t.w = f.w;\n  t.X = f.X.slice();\n  return t;\n};\n\nfunction impl(seed, opts) {\n  if (seed == null) seed = +(new Date);\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (state.X) copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.xor4096 = impl;\n}\n\n})(\n  this,                                     // window object or global\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n", "// A Javascript implementaion of the \"Tyche-i\" prng algorithm by\n// Samuel Neves and Filipe Araujo.\n// See https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n\n(function(global, module, define) {\n\nfunction XorGen(seed) {\n  var me = this, strseed = '';\n\n  // Set up generator function.\n  me.next = function() {\n    var b = me.b, c = me.c, d = me.d, a = me.a;\n    b = (b << 25) ^ (b >>> 7) ^ c;\n    c = (c - d) | 0;\n    d = (d << 24) ^ (d >>> 8) ^ a;\n    a = (a - b) | 0;\n    me.b = b = (b << 20) ^ (b >>> 12) ^ c;\n    me.c = c = (c - d) | 0;\n    me.d = (d << 16) ^ (c >>> 16) ^ a;\n    return me.a = (a - b) | 0;\n  };\n\n  /* The following is non-inverted tyche, which has better internal\n   * bit diffusion, but which is about 25% slower than tyche-i in JS.\n  me.next = function() {\n    var a = me.a, b = me.b, c = me.c, d = me.d;\n    a = (me.a + me.b | 0) >>> 0;\n    d = me.d ^ a; d = d << 16 ^ d >>> 16;\n    c = me.c + d | 0;\n    b = me.b ^ c; b = b << 12 ^ d >>> 20;\n    me.a = a = a + b | 0;\n    d = d ^ a; me.d = d = d << 8 ^ d >>> 24;\n    me.c = c = c + d | 0;\n    b = b ^ c;\n    return me.b = (b << 7 ^ b >>> 25);\n  }\n  */\n\n  me.a = 0;\n  me.b = 0;\n  me.c = 2654435769 | 0;\n  me.d = 1367130551;\n\n  if (seed === Math.floor(seed)) {\n    // Integer seed.\n    me.a = (seed / 0x100000000) | 0;\n    me.b = seed | 0;\n  } else {\n    // String seed.\n    strseed += seed;\n  }\n\n  // Mix in string seed, then discard an initial batch of 64 values.\n  for (var k = 0; k < strseed.length + 20; k++) {\n    me.b ^= strseed.charCodeAt(k) | 0;\n    me.next();\n  }\n}\n\nfunction copy(f, t) {\n  t.a = f.a;\n  t.b = f.b;\n  t.c = f.c;\n  t.d = f.d;\n  return t;\n};\n\nfunction impl(seed, opts) {\n  var xg = new XorGen(seed),\n      state = opts && opts.state,\n      prng = function() { return (xg.next() >>> 0) / 0x100000000; };\n  prng.double = function() {\n    do {\n      var top = xg.next() >>> 11,\n          bot = (xg.next() >>> 0) / 0x100000000,\n          result = (top + bot) / (1 << 21);\n    } while (result === 0);\n    return result;\n  };\n  prng.int32 = xg.next;\n  prng.quick = prng;\n  if (state) {\n    if (typeof(state) == 'object') copy(state, xg);\n    prng.state = function() { return copy(xg, {}); }\n  }\n  return prng;\n}\n\nif (module && module.exports) {\n  module.exports = impl;\n} else if (define && define.amd) {\n  define(function() { return impl; });\n} else {\n  this.tychei = impl;\n}\n\n})(\n  this,\n  (typeof module) == 'object' && module,    // present in node.js\n  (typeof define) == 'function' && define   // present with an AMD loader\n);\n\n\n", "/*\nCopyright 2019 David Bau.\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be\nincluded in all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n*/\n\n(function (global, pool, math) {\n//\n// The following constants are related to IEEE 754 limits.\n//\n\nvar width = 256,        // each RC4 output is 0 <= x < 256\n    chunks = 6,         // at least six RC4 outputs for each double\n    digits = 52,        // there are 52 significant digits in a double\n    rngname = 'random', // rngname: name for Math.random and Math.seedrandom\n    startdenom = math.pow(width, chunks),\n    significance = math.pow(2, digits),\n    overflow = significance * 2,\n    mask = width - 1,\n    nodecrypto;         // node.js crypto module, initialized at the bottom.\n\n//\n// seedrandom()\n// This is the seedrandom function described above.\n//\nfunction seedrandom(seed, options, callback) {\n  var key = [];\n  options = (options == true) ? { entropy: true } : (options || {});\n\n  // Flatten the seed string or build one from local entropy if needed.\n  var shortseed = mixkey(flatten(\n    options.entropy ? [seed, tostring(pool)] :\n    (seed == null) ? autoseed() : seed, 3), key);\n\n  // Use the seed to initialize an ARC4 generator.\n  var arc4 = new ARC4(key);\n\n  // This function returns a random double in [0, 1) that contains\n  // randomness in every bit of the mantissa of the IEEE 754 value.\n  var prng = function() {\n    var n = arc4.g(chunks),             // Start with a numerator n < 2 ^ 48\n        d = startdenom,                 //   and denominator d = 2 ^ 48.\n        x = 0;                          //   and no 'extra last byte'.\n    while (n < significance) {          // Fill up all significant digits by\n      n = (n + x) * width;              //   shifting numerator and\n      d *= width;                       //   denominator and generating a\n      x = arc4.g(1);                    //   new least-significant-byte.\n    }\n    while (n >= overflow) {             // To avoid rounding up, before adding\n      n /= 2;                           //   last byte, shift everything\n      d /= 2;                           //   right using integer math until\n      x >>>= 1;                         //   we have exactly the desired bits.\n    }\n    return (n + x) / d;                 // Form the number within [0, 1).\n  };\n\n  prng.int32 = function() { return arc4.g(4) | 0; }\n  prng.quick = function() { return arc4.g(4) / 0x100000000; }\n  prng.double = prng;\n\n  // Mix the randomness into accumulated entropy.\n  mixkey(tostring(arc4.S), pool);\n\n  // Calling convention: what to return as a function of prng, seed, is_math.\n  return (options.pass || callback ||\n      function(prng, seed, is_math_call, state) {\n        if (state) {\n          // Load the arc4 state from the given state if it has an S array.\n          if (state.S) { copy(state, arc4); }\n          // Only provide the .state method if requested via options.state.\n          prng.state = function() { return copy(arc4, {}); }\n        }\n\n        // If called as a method of Math (Math.seedrandom()), mutate\n        // Math.random because that is how seedrandom.js has worked since v1.0.\n        if (is_math_call) { math[rngname] = prng; return seed; }\n\n        // Otherwise, it is a newer calling convention, so return the\n        // prng directly.\n        else return prng;\n      })(\n  prng,\n  shortseed,\n  'global' in options ? options.global : (this == math),\n  options.state);\n}\n\n//\n// ARC4\n//\n// An ARC4 implementation.  The constructor takes a key in the form of\n// an array of at most (width) integers that should be 0 <= x < (width).\n//\n// The g(count) method returns a pseudorandom integer that concatenates\n// the next (count) outputs from ARC4.  Its return value is a number x\n// that is in the range 0 <= x < (width ^ count).\n//\nfunction ARC4(key) {\n  var t, keylen = key.length,\n      me = this, i = 0, j = me.i = me.j = 0, s = me.S = [];\n\n  // The empty key [] is treated as [0].\n  if (!keylen) { key = [keylen++]; }\n\n  // Set up S using the standard key scheduling algorithm.\n  while (i < width) {\n    s[i] = i++;\n  }\n  for (i = 0; i < width; i++) {\n    s[i] = s[j = mask & (j + key[i % keylen] + (t = s[i]))];\n    s[j] = t;\n  }\n\n  // The \"g\" method returns the next (count) outputs as one number.\n  (me.g = function(count) {\n    // Using instance members instead of closure state nearly doubles speed.\n    var t, r = 0,\n        i = me.i, j = me.j, s = me.S;\n    while (count--) {\n      t = s[i = mask & (i + 1)];\n      r = r * width + s[mask & ((s[i] = s[j = mask & (j + t)]) + (s[j] = t))];\n    }\n    me.i = i; me.j = j;\n    return r;\n    // For robust unpredictability, the function call below automatically\n    // discards an initial batch of values.  This is called RC4-drop[256].\n    // See http://google.com/search?q=rsa+fluhrer+response&btnI\n  })(width);\n}\n\n//\n// copy()\n// Copies internal state of ARC4 to or from a plain object.\n//\nfunction copy(f, t) {\n  t.i = f.i;\n  t.j = f.j;\n  t.S = f.S.slice();\n  return t;\n};\n\n//\n// flatten()\n// Converts an object tree to nested arrays of strings.\n//\nfunction flatten(obj, depth) {\n  var result = [], typ = (typeof obj), prop;\n  if (depth && typ == 'object') {\n    for (prop in obj) {\n      try { result.push(flatten(obj[prop], depth - 1)); } catch (e) {}\n    }\n  }\n  return (result.length ? result : typ == 'string' ? obj : obj + '\\0');\n}\n\n//\n// mixkey()\n// Mixes a string seed into a key that is an array of integers, and\n// returns a shortened string seed that is equivalent to the result key.\n//\nfunction mixkey(seed, key) {\n  var stringseed = seed + '', smear, j = 0;\n  while (j < stringseed.length) {\n    key[mask & j] =\n      mask & ((smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++));\n  }\n  return tostring(key);\n}\n\n//\n// autoseed()\n// Returns an object for autoseeding, using window.crypto and Node crypto\n// module if available.\n//\nfunction autoseed() {\n  try {\n    var out;\n    if (nodecrypto && (out = nodecrypto.randomBytes)) {\n      // The use of 'out' to remember randomBytes makes tight minified code.\n      out = out(width);\n    } else {\n      out = new Uint8Array(width);\n      (global.crypto || global.msCrypto).getRandomValues(out);\n    }\n    return tostring(out);\n  } catch (e) {\n    var browser = global.navigator,\n        plugins = browser && browser.plugins;\n    return [+new Date, global, plugins, global.screen, tostring(pool)];\n  }\n}\n\n//\n// tostring()\n// Converts an array of charcodes to a string\n//\nfunction tostring(a) {\n  return String.fromCharCode.apply(0, a);\n}\n\n//\n// When seedrandom.js is loaded, we immediately mix a few bits\n// from the built-in RNG into the entropy pool.  Because we do\n// not want to interfere with deterministic PRNG state later,\n// seedrandom will not call math.random on its own again after\n// initialization.\n//\nmixkey(math.random(), pool);\n\n//\n// Nodejs and AMD support: export the implementation as a module using\n// either convention.\n//\nif ((typeof module) == 'object' && module.exports) {\n  module.exports = seedrandom;\n  // When in node.js, try using crypto package for autoseeding.\n  try {\n    nodecrypto = require('crypto');\n  } catch (ex) {}\n} else if ((typeof define) == 'function' && define.amd) {\n  define(function() { return seedrandom; });\n} else {\n  // When included as a plain script, set up Math.seedrandom global.\n  math['seed' + rngname] = seedrandom;\n}\n\n\n// End anonymous scope, and pass initial values.\n})(\n  // global: `self` in browsers (including strict mode and web workers),\n  // otherwise `this` in Node and other environments\n  (typeof self !== 'undefined') ? self : this,\n  [],     // pool: entropy pool starts empty\n  Math    // math: package containing random, pow, and seedrandom\n);\n", "// A library of seedable RNGs implemented in Javascript.\n//\n// Usage:\n//\n// var seedrandom = require('seedrandom');\n// var random = seedrandom(1); // or any seed.\n// var x = random();       // 0 <= x < 1.  Every bit is random.\n// var x = random.quick(); // 0 <= x < 1.  32 bits of randomness.\n\n// alea, a 53-bit multiply-with-carry generator by Johannes Baag\u00F8e.\n// Period: ~2^116\n// Reported to pass all BigCrush tests.\nvar alea = require('./lib/alea');\n\n// xor128, a pure xor-shift generator by George Marsaglia.\n// Period: 2^128-1.\n// Reported to fail: MatrixRank and LinearComp.\nvar xor128 = require('./lib/xor128');\n\n// xorwow, George Marsaglia's 160-bit xor-shift combined plus weyl.\n// Period: 2^192-2^32\n// Reported to fail: CollisionOver, SimpPoker, and LinearComp.\nvar xorwow = require('./lib/xorwow');\n\n// xorshift7, by Fran\u00E7ois Panneton and Pierre L'ecuyer, takes\n// a different approach: it adds robustness by allowing more shifts\n// than Marsaglia's original three.  It is a 7-shift generator\n// with 256 bits, that passes BigCrush with no systmatic failures.\n// Period 2^256-1.\n// No systematic BigCrush failures reported.\nvar xorshift7 = require('./lib/xorshift7');\n\n// xor4096, by Richard Brent, is a 4096-bit xor-shift with a\n// very long period that also adds a Weyl generator. It also passes\n// BigCrush with no systematic failures.  Its long period may\n// be useful if you have many generators and need to avoid\n// collisions.\n// Period: 2^4128-2^32.\n// No systematic BigCrush failures reported.\nvar xor4096 = require('./lib/xor4096');\n\n// Tyche-i, by Samuel Neves and Filipe Araujo, is a bit-shifting random\n// number generator derived from ChaCha, a modern stream cipher.\n// https://eden.dei.uc.pt/~sneves/pubs/2011-snfa2.pdf\n// Period: ~2^127\n// No systematic BigCrush failures reported.\nvar tychei = require('./lib/tychei');\n\n// The original ARC4-based prng included in this library.\n// Period: ~2^1600\nvar sr = require('./seedrandom');\n\nsr.alea = alea;\nsr.xor128 = xor128;\nsr.xorwow = xorwow;\nsr.xorshift7 = xorshift7;\nsr.xor4096 = xor4096;\nsr.tychei = tychei;\n\nmodule.exports = sr;\n", "", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, 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null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "export const wasmWorkerContents = 'var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;this.alert=threadAlert;Module[\"instantiateWasm\"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);Module[\"wasmModule\"]=null;receiveInstance(instance);return instance.exports};function moduleLoaded(){}this.onmessage=function(e){try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance;moduleLoaded()})}else if(e.data.cmd===\"objectTransfer\"){Module[\"PThread\"].receiveObjectTransfer(e.data)}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0);var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module[\"establishStackSpace\"](top,max);Module[\"_emscripten_tls_init\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].setThreadStatus(Module[\"_pthread_self\"](),1);try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(!Module[\"getNoExitRuntime\"]())Module[\"PThread\"].threadExit(result)}catch(ex){if(ex===\"Canceled!\"){Module[\"PThread\"].threadCancel()}else if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"getNoExitRuntime\"]()){}else{Module[\"PThread\"].threadExit(ex.status)}}else{Module[\"PThread\"].threadExit(-2);throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"PThread\"].threadCancel()}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);throw ex}};if(typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require(\"worker_threads\");global.Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var nodeFS=require(\"fs\");var nodeRead=function(filename){return nodeFS.readFileSync(filename,\"utf8\")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance===\"undefined\"){performance={now:function(){return Date.now()}}}}';", null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, null, "// wrapper to load tfjs in a single place so version can be changed quickly\n\n// simplified\n// { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }\n\n// export * from '@tensorflow/tfjs/dist/index.js';\n// export * from '@tensorflow/tfjs-backend-wasm';\n\n// modular\n// { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }\n\n// get versions of all packages.\nimport * as packageBundle from '@tensorflow/tfjs/package.json';\nimport * as packageCore from '@tensorflow/tfjs-core/package.json';\nimport * as packageData from '@tensorflow/tfjs-data/package.json';\nimport * as packageLayers from '@tensorflow/tfjs-layers/package.json';\nimport * as packageConverter from '@tensorflow/tfjs-converter/package.json';\n// for backends, get version from source so it can register backend during import\nimport { version_cpu } from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nimport { version_webgl } from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nimport { version_wasm } from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export all\nexport * from '@tensorflow/tfjs-core/dist/index.js';\nexport * from '@tensorflow/tfjs-layers/dist/index.js';\nexport * from '@tensorflow/tfjs-converter/dist/index.js';\nexport * as data from '@tensorflow/tfjs-data/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-cpu/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-webgl/dist/index.js';\nexport * from '@tensorflow/tfjs-backend-wasm/dist/index.js';\n\n// export versions\nexport const version = {\n  tfjs: packageBundle.version,\n  'tfjs-core': packageCore.version,\n  'tfjs-data': packageData.version,\n  'tfjs-layers': packageLayers.version,\n  'tfjs-converter': packageConverter.version,\n  'tfjs-backend-cpu': version_cpu,\n  'tfjs-backend-webgl': version_webgl,\n  'tfjs-backend-wasm': version_wasm,\n};\n"],
+  "mappings": 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   "names": []
 }
diff --git a/human.service b/human.service
index 08399b5f..6cf5d098 100644
--- a/human.service
+++ b/human.service
@@ -5,8 +5,8 @@ After=network.target network-online.target
 [Service]
 Type=simple
 Environment="NODE_ENV=production"
-ExecStart=/home/vlado/.nvm/versions/node/v15.7.0/bin/node server/serve.js
-WorkingDirectory=/home/vlado/dev/human
+ExecStart=<path-to-node> server/serve.js
+WorkingDirectory=<your-project-folder>
 StandardOutput=inherit
 StandardError=inherit
 Restart=always
diff --git a/package-lock.json b/package-lock.json
deleted file mode 100644
index 92ad5090..00000000
--- a/package-lock.json
+++ /dev/null
@@ -1,7790 +0,0 @@
-{
-  "name": "@vladmandic/human",
-  "version": "1.1.8",
-  "lockfileVersion": 2,
-  "requires": true,
-  "packages": {
-    "": {
-      "name": "@vladmandic/human",
-      "version": "1.1.8",
-      "license": "MIT",
-      "devDependencies": {
-        "@microsoft/api-extractor": "^7.13.2",
-        "@tensorflow/tfjs": "^3.3.0",
-        "@tensorflow/tfjs-backend-cpu": "^3.3.0",
-        "@tensorflow/tfjs-backend-wasm": "^3.3.0",
-        "@tensorflow/tfjs-backend-webgl": "^3.3.0",
-        "@tensorflow/tfjs-converter": "^3.3.0",
-        "@tensorflow/tfjs-core": "^3.3.0",
-        "@tensorflow/tfjs-data": "^3.3.0",
-        "@tensorflow/tfjs-layers": "^3.3.0",
-        "@tensorflow/tfjs-node": "^3.3.0",
-        "@tensorflow/tfjs-node-gpu": "^3.3.0",
-        "@types/node": "^14.14.35",
-        "@typescript-eslint/eslint-plugin": "^4.18.0",
-        "@typescript-eslint/parser": "^4.18.0",
-        "@vladmandic/pilogger": "^0.2.14",
-        "chokidar": "^3.5.1",
-        "dayjs": "^1.10.4",
-        "esbuild": "^0.9.3",
-        "eslint": "^7.22.0",
-        "eslint-config-airbnb-base": "^14.2.1",
-        "eslint-plugin-import": "^2.22.1",
-        "eslint-plugin-json": "^2.1.2",
-        "eslint-plugin-node": "^11.1.0",
-        "eslint-plugin-promise": "^4.3.1",
-        "rimraf": "^3.0.2",
-        "seedrandom": "^3.0.5",
-        "simple-git": "^2.37.0",
-        "tslib": "^2.1.0",
-        "typedoc": "^0.20.32",
-        "typescript": "^4.2.3"
-      },
-      "engines": {
-        "node": ">=12.0.0"
-      }
-    },
-    "node_modules/@babel/code-frame": {
-      "version": "7.12.11",
-      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.12.11.tgz",
-      "integrity": "sha512-Zt1yodBx1UcyiePMSkWnU4hPqhwq7hGi2nFL1LeA3EUl+q2LQx16MISgJ0+z7dnmgvP9QtIleuETGOiOH1RcIw==",
-      "dev": true,
-      "dependencies": {
-        "@babel/highlight": "^7.10.4"
-      }
-    },
-    "node_modules/@babel/helper-validator-identifier": {
-      "version": "7.12.11",
-      "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.12.11.tgz",
-      "integrity": "sha512-np/lG3uARFybkoHokJUmf1QfEvRVCPbmQeUQpKow5cQ3xWrV9i3rUHodKDJPQfTVX61qKi+UdYk8kik84n7XOw==",
-      "dev": true
-    },
-    "node_modules/@babel/highlight": {
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diff --git a/src/blazeface/facemesh.ts b/src/blazeface/facemesh.ts
index 7ca6cbe1..75439563 100644
--- a/src/blazeface/facemesh.ts
+++ b/src/blazeface/facemesh.ts
@@ -31,22 +31,22 @@ export class MediaPipeFaceMesh {
       const box = prediction.box ? [
         Math.max(0, prediction.box.startPoint[0]),
         Math.max(0, prediction.box.startPoint[1]),
-        Math.min(input.shape[1], prediction.box.endPoint[0]) - prediction.box.startPoint[0],
-        Math.min(input.shape[2], prediction.box.endPoint[1]) - prediction.box.startPoint[1],
+        Math.min(input.shape[1], prediction.box.endPoint[0]) - Math.max(0, prediction.box.startPoint[0]),
+        Math.min(input.shape[2], prediction.box.endPoint[1]) - Math.max(0, prediction.box.startPoint[1]),
       ] : 0;
       const boxRaw = prediction.box ? [
-        Math.max(0, prediction.box.startPoint[0] / input.shape[2]),
-        Math.max(0, prediction.box.startPoint[1] / input.shape[1]),
-        Math.min(input.shape[1], (prediction.box.endPoint[0]) - prediction.box.startPoint[0]) / input.shape[2],
-        Math.min(input.shape[2], (prediction.box.endPoint[1]) - prediction.box.startPoint[1]) / input.shape[1],
+        prediction.box.startPoint[0] / input.shape[2],
+        prediction.box.startPoint[1] / input.shape[1],
+        (prediction.box.endPoint[0] - prediction.box.startPoint[0]) / input.shape[2],
+        (prediction.box.endPoint[1] - prediction.box.startPoint[1]) / input.shape[1],
       ] : [];
       results.push({
         confidence: prediction.faceConfidence || prediction.boxConfidence || 0,
         boxConfidence: prediction.boxConfidence,
         faceConfidence: prediction.faceConfidence,
         box,
-        mesh,
         boxRaw,
+        mesh,
         meshRaw,
         annotations,
         image: prediction.image ? prediction.image.clone() : null,
diff --git a/src/draw.ts b/src/draw.ts
index 9ee6bd75..ee6f1862 100644
--- a/src/draw.ts
+++ b/src/draw.ts
@@ -18,6 +18,7 @@ export const drawOptions = {
   useDepth: <Boolean>true,
   useCurves: <Boolean>false,
   bufferedOutput: <Boolean>false,
+  useRawBoxes: <Boolean>false,
 };
 
 function point(ctx, x, y, z = null) {
@@ -121,8 +122,8 @@ export async function face(inCanvas, result) {
     ctx.strokeStyle = drawOptions.color;
     ctx.fillStyle = drawOptions.color;
     if (drawOptions.drawBoxes) {
-      rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);
-      // rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);
+      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * f.boxRaw[0], inCanvas.height * f.boxRaw[1], inCanvas.width * f.boxRaw[2], inCanvas.height * f.boxRaw[3]);
+      else rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3]);
     }
     // silly hack since fillText does not suport new line
     const labels:string[] = [];
@@ -305,7 +306,8 @@ export async function hand(inCanvas, result) {
     if (drawOptions.drawBoxes) {
       ctx.strokeStyle = drawOptions.color;
       ctx.fillStyle = drawOptions.color;
-      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);
+      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);
+      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);
       if (drawOptions.drawLabels) {
         if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {
           ctx.fillStyle = drawOptions.shadowColor;
@@ -357,7 +359,8 @@ export async function object(inCanvas, result) {
     if (drawOptions.drawBoxes) {
       ctx.strokeStyle = drawOptions.color;
       ctx.fillStyle = drawOptions.color;
-      rect(ctx, h.box[0], h.box[1], h.box[2] - h.box[0], h.box[3] - h.box[1]);
+      if (drawOptions.useRawBoxes) rect(ctx, inCanvas.width * h.boxRaw[0], inCanvas.height * h.boxRaw[1], inCanvas.width * h.boxRaw[2], inCanvas.height * h.boxRaw[3]);
+      else rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3]);
       if (drawOptions.drawLabels) {
         const label = `${Math.round(100 * h.score)}% ${h.label}`;
         if (drawOptions.shadowColor && drawOptions.shadowColor !== '') {
diff --git a/src/handpose/handpose.ts b/src/handpose/handpose.ts
index 80b6f758..98ca38d0 100644
--- a/src/handpose/handpose.ts
+++ b/src/handpose/handpose.ts
@@ -29,7 +29,7 @@ export class HandPose {
   async estimateHands(input, config) {
     const predictions = await this.handPipeline.estimateHands(input, config);
     if (!predictions) return [];
-    const hands: Array<{ confidence: number, box: any, landmarks: any, annotations: any }> = [];
+    const hands: Array<{ confidence: number, box: any, boxRaw: any, landmarks: any, annotations: any }> = [];
     for (const prediction of predictions) {
       const annotations = {};
       if (prediction.landmarks) {
@@ -40,10 +40,16 @@ export class HandPose {
       const box = prediction.box ? [
         Math.max(0, prediction.box.topLeft[0]),
         Math.max(0, prediction.box.topLeft[1]),
-        Math.min(input.shape[2], prediction.box.bottomRight[0]) - prediction.box.topLeft[0],
-        Math.min(input.shape[1], prediction.box.bottomRight[1]) - prediction.box.topLeft[1],
-      ] : 0;
-      hands.push({ confidence: prediction.confidence, box, landmarks: prediction.landmarks, annotations });
+        Math.min(input.shape[2], prediction.box.bottomRight[0]) - Math.max(0, prediction.box.topLeft[0]),
+        Math.min(input.shape[1], prediction.box.bottomRight[1]) - Math.max(0, prediction.box.topLeft[1]),
+      ] : [];
+      const boxRaw = [
+        (prediction.box.topLeft[0]) / input.shape[2],
+        (prediction.box.topLeft[1]) / input.shape[1],
+        (prediction.box.bottomRight[0] - prediction.box.topLeft[0]) / input.shape[2],
+        (prediction.box.bottomRight[1] - prediction.box.topLeft[1]) / input.shape[1],
+      ];
+      hands.push({ confidence: prediction.confidence, box, boxRaw, landmarks: prediction.landmarks, annotations });
     }
     return hands;
   }
diff --git a/src/human.ts b/src/human.ts
index 8ee31bd4..8b8d7297 100644
--- a/src/human.ts
+++ b/src/human.ts
@@ -54,6 +54,7 @@ export type Result = {
   hand: Array<{
     confidence: Number,
     box: [Number, Number, Number, Number],
+    boxRaw: [Number, Number, Number, Number],
     landmarks: Array<[Number, Number, Number]>,
     annotations: Array<{ part: String, points: Array<[Number, Number, Number]>[] }>,
   }>,
@@ -595,7 +596,17 @@ export class Human {
 
       this.#perf.total = Math.trunc(now() - timeStart);
       this.state = 'idle';
-      resolve({ face: faceRes, body: bodyRes, hand: handRes, gesture: gestureRes, object: objectRes, performance: this.#perf, canvas: process.canvas });
+      const result = {
+        face: faceRes,
+        body: bodyRes,
+        hand: handRes,
+        gesture: gestureRes,
+        object: objectRes,
+        performance: this.#perf,
+        canvas: process.canvas,
+      };
+      // log('Result:', result);
+      resolve(result);
     });
   }
 
diff --git a/src/nanodet/nanodet.ts b/src/nanodet/nanodet.ts
index 562519e6..38fb6f80 100644
--- a/src/nanodet/nanodet.ts
+++ b/src/nanodet/nanodet.ts
@@ -49,10 +49,10 @@ async function process(res, inputSize, outputShape, config) {
           ];
           boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))); // fix out-of-bounds coords
           const box = [ // results normalized to input image pixels
-            boxRaw[0] * outputShape[0],
-            boxRaw[1] * outputShape[1],
-            boxRaw[2] * outputShape[0],
-            boxRaw[3] * outputShape[1],
+            Math.max(0, (boxRaw[0] * outputShape[0])),
+            Math.max(0, (boxRaw[1] * outputShape[1])),
+            Math.min(1, (boxRaw[2] * outputShape[0]) - (boxRaw[0] * outputShape[0])),
+            Math.min(1, (boxRaw[3] * outputShape[1]) - (boxRaw[1] * outputShape[1])),
           ];
           const result = {
             score: scoresMax[i],
diff --git a/typedoc/assets/js/search.js b/typedoc/assets/js/search.js
index 52b7681a..32bd04a9 100644
--- a/typedoc/assets/js/search.js
+++ b/typedoc/assets/js/search.js
@@ -1 +1 @@
-window.searchData = {"kinds":{"128":"Class","512":"Constructor","1024":"Property","2048":"Method","65536":"Type literal","4194304":"Type alias","16777216":"Reference"},"rows":[{"id":0,"kind":4194304,"name":"Result","url":"index.html#result","classes":"tsd-kind-type-alias"},{"id":1,"kind":65536,"name":"__type","url":"index.html#result.__type","classes":"tsd-kind-type-literal tsd-parent-kind-type-alias","parent":"Result"},{"id":2,"kind":1024,"name":"face","url":"index.html#result.__type.face","classes":"tsd-kind-property tsd-parent-kind-type-literal","parent":"Result.__type"},{"id":3,"kind":1024,"name":"body","url":"index.html#result.__type.body","classes":"tsd-kind-property tsd-parent-kind-type-literal","parent":"Result.__type"},{"id":4,"kind":1024,"name":"hand","url":"index.html#result.__type.hand","classes":"tsd-kind-property tsd-parent-kind-type-literal","parent":"Result.__type"},{"id":5,"kind":1024,"name":"gesture","url":"index.html#result.__type.gesture","classes":"tsd-kind-property tsd-parent-kind-type-literal","parent":"Result.__type"},{"id":6,"kind":1024,"name":"object","url":"index.html#result.__type.object","classes":"tsd-kind-property tsd-parent-kind-type-literal","parent":"Result.__type"},{"id":7,"kind":1024,"name":"performance","url":"index.html#result.__type.performance","classes":"tsd-kind-property tsd-parent-kind-type-literal","parent":"Result.__type"},{"id":8,"kind":65536,"name":"__type","url":"index.html#result.__type.__type-1","classes":"tsd-kind-type-literal tsd-parent-kind-type-literal","parent":"Result.__type"},{"id":9,"kind":1024,"name":"any","url":"index.html#result.__type.__type-1.any","classes":"tsd-kind-property tsd-parent-kind-type-literal","parent":"Result.__type.__type"},{"id":10,"kind":1024,"name":"canvas","url":"index.html#result.__type.canvas","classes":"tsd-kind-property tsd-parent-kind-type-literal","parent":"Result.__type"},{"id":11,"kind":128,"name":"Human","url":"classes/human.html","classes":"tsd-kind-class"},{"id":12,"kind":512,"name":"constructor","url":"classes/human.html#constructor","classes":"tsd-kind-constructor tsd-parent-kind-class","parent":"Human"},{"id":13,"kind":1024,"name":"version","url":"classes/human.html#version","classes":"tsd-kind-property tsd-parent-kind-class","parent":"Human"},{"id":14,"kind":1024,"name":"config","url":"classes/human.html#config","classes":"tsd-kind-property tsd-parent-kind-class","parent":"Human"},{"id":15,"kind":65536,"name":"__type","url":"classes/human.html#__type-1","classes":"tsd-kind-type-literal tsd-parent-kind-class","parent":"Human"},{"id":16,"kind":1024,"name":"backend","url":"classes/human.html#__type-1.backend","classes":"tsd-kind-property 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diff --git a/typedoc/classes/human.html b/typedoc/classes/human.html
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@@ -488,7 +488,7 @@
 				<section class="tsd-panel tsd-member tsd-kind-property tsd-parent-kind-class">
 					<a name="draw" class="tsd-anchor"></a>
 					<h3>draw</h3>
-					<div class="tsd-signature tsd-kind-icon">draw<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">{ </span>all<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>body<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>drawOptions<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-symbol">{ </span>bufferedOutput<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>color<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>drawBoxes<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawLabels<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawPoints<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawPolygons<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>fillPolygons<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>font<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>labelColor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>lineHeight<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>lineWidth<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>pointSize<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>roundRect<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>shadowColor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>useCurves<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>useDepth<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">; </span>face<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol"> }</span></div>
+					<div class="tsd-signature tsd-kind-icon">draw<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">{ </span>all<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>body<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>drawOptions<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-symbol">{ </span>bufferedOutput<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>color<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>drawBoxes<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawLabels<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawPoints<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawPolygons<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>fillPolygons<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>font<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>labelColor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>lineHeight<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>lineWidth<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>pointSize<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>roundRect<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>shadowColor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>useCurves<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>useDepth<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>useRawBoxes<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">; </span>face<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol">; </span>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span><span class="tsd-signature-symbol"> }</span></div>
 					<aside class="tsd-sources">
 					</aside>
 					<div class="tsd-type-declaration">
@@ -504,7 +504,7 @@
 								<h5>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Function</span></h5>
 							</li>
 							<li class="tsd-parameter">
-								<h5><span class="tsd-flag ts-flagOptional">Optional</span> draw<wbr>Options<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-symbol">{ </span>bufferedOutput<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>color<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>drawBoxes<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawLabels<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawPoints<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawPolygons<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>fillPolygons<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>font<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>labelColor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>lineHeight<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>lineWidth<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>pointSize<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>roundRect<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>shadowColor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>useCurves<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>useDepth<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol"> }</span></h5>
+								<h5><span class="tsd-flag ts-flagOptional">Optional</span> draw<wbr>Options<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-symbol">{ </span>bufferedOutput<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>color<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>drawBoxes<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawLabels<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawPoints<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>drawPolygons<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>fillPolygons<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>font<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>labelColor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>lineHeight<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>lineWidth<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>pointSize<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>roundRect<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>shadowColor<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>useCurves<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>useDepth<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol">; </span>useRawBoxes<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span><span class="tsd-signature-symbol"> }</span></h5>
 								<ul class="tsd-parameters">
 									<li class="tsd-parameter">
 										<h5>buffered<wbr>Output<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span></h5>
@@ -554,6 +554,9 @@
 									<li class="tsd-parameter">
 										<h5>use<wbr>Depth<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span></h5>
 									</li>
+									<li class="tsd-parameter">
+										<h5>use<wbr>Raw<wbr>Boxes<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Boolean</span></h5>
+									</li>
 								</ul>
 							</li>
 							<li class="tsd-parameter">
diff --git a/typedoc/index.html b/typedoc/index.html
index 41c82711..125156ab 100644
--- a/typedoc/index.html
+++ b/typedoc/index.html
@@ -99,7 +99,7 @@
 				<section class="tsd-panel tsd-member tsd-kind-type-alias">
 					<a name="result" class="tsd-anchor"></a>
 					<h3>Result</h3>
-					<div class="tsd-signature tsd-kind-icon">Result<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">{ </span>body<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>id<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>position<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>x<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>y<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>z<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">; </span>presence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>score<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol">; </span>face<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>age<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>angle<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>pitch<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>roll<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>yaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">; </span>annotations<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>points<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>box<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>boxConfidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>boxRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>confidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>emotion<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>emotion<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>score<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>faceConfidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>gender<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>genderConfidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>iris<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>mesh<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>meshRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>annotations<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>points<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>box<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>confidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>landmarks<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>object<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>box<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>boxRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>center<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>centerRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>class<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>label<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>score<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>strideSize<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>performance<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>any<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol"> }</span></div>
+					<div class="tsd-signature tsd-kind-icon">Result<span class="tsd-signature-symbol">:</span> <span class="tsd-signature-symbol">{ </span>body<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>id<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>position<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>x<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>y<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>z<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">; </span>presence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>score<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>canvas<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">OffscreenCanvas</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLCanvasElement</span><span class="tsd-signature-symbol">; </span>face<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>age<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>angle<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>pitch<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>roll<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>yaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">; </span>annotations<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>points<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>box<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>boxConfidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>boxRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>confidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>embedding<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>emotion<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>emotion<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>score<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>faceConfidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>gender<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>genderConfidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>iris<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>mesh<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>meshRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>annotations<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>points<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>box<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>boxRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>confidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>landmarks<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>object<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>box<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>boxRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>center<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>centerRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>class<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>label<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>score<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>strideSize<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>performance<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>any<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">any</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol"> }</span></div>
 					<aside class="tsd-sources">
 					</aside>
 					<div class="tsd-type-declaration">
@@ -118,7 +118,7 @@
 								<h5>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>gesture<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span></h5>
 							</li>
 							<li class="tsd-parameter">
-								<h5>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>annotations<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>points<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>box<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>confidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>landmarks<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span></h5>
+								<h5>hand<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>annotations<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>part<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>points<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>box<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>boxRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">; </span>confidence<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>landmarks<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">[</span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">]</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span></h5>
 							</li>
 							<li class="tsd-parameter">
 								<h5>object<span class="tsd-signature-symbol">: </span><span class="tsd-signature-symbol">{ </span>box<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>boxRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>center<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>centerRaw<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">; </span>class<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>label<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">String</span><span class="tsd-signature-symbol">; </span>score<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol">; </span>strideSize<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span></h5>
diff --git a/types/src/draw.d.ts b/types/src/draw.d.ts
index e87dc350..48c93204 100644
--- a/types/src/draw.d.ts
+++ b/types/src/draw.d.ts
@@ -15,6 +15,7 @@ export declare const drawOptions: {
     useDepth: Boolean;
     useCurves: Boolean;
     bufferedOutput: Boolean;
+    useRawBoxes: Boolean;
 };
 export declare function gesture(inCanvas: any, result: any): Promise<void>;
 export declare function face(inCanvas: any, result: any): Promise<void>;
diff --git a/types/src/handpose/handpose.d.ts b/types/src/handpose/handpose.d.ts
index dac79315..ffbdd1f5 100644
--- a/types/src/handpose/handpose.d.ts
+++ b/types/src/handpose/handpose.d.ts
@@ -12,6 +12,7 @@ export declare class HandPose {
     estimateHands(input: any, config: any): Promise<{
         confidence: number;
         box: any;
+        boxRaw: any;
         landmarks: any;
         annotations: any;
     }[]>;
diff --git a/types/src/human.d.ts b/types/src/human.d.ts
index fcbab15f..8a07d4b7 100644
--- a/types/src/human.d.ts
+++ b/types/src/human.d.ts
@@ -53,6 +53,7 @@ export declare type Result = {
     hand: Array<{
         confidence: Number;
         box: [Number, Number, Number, Number];
+        boxRaw: [Number, Number, Number, Number];
         landmarks: Array<[Number, Number, Number]>;
         annotations: Array<{
             part: String;
diff --git a/wiki b/wiki
index 99c3d70e..91af84e9 160000
--- a/wiki
+++ b/wiki
@@ -1 +1 @@
-Subproject commit 99c3d70ec78fbbe0d12528c1d4b18ba1d27fef0d
+Subproject commit 91af84e9543762c4f31be41dda15fb2a5549d8a6